Journal of Experimental Botany, Vol. 65, No. 13, pp. 3443–3457, 2014
doi:10.1093/jxb/eru157 Advance Access publication 22 April, 2014
Review paper
Bundle-sheath leakiness in C4 photosynthesis: a careful
balancing act between CO2 concentration and assimilation
Johannes Kromdijk1,*, Nerea Ubierna2, Asaph B. Cousins3 and Howard Griffiths4
1 Institute for Genomic Biology, University of Illinois, 1206 W Gregory drive, Urbana, IL 61801, USA
Research School of Biology, The Australian National University, Canberra, ACT, Australia
3 School of Biological Sciences, Washington State University, Pullman, WA99164-4236, USA
4 Physiological Ecology Group, Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB23EA, UK
2 * To whom correspondence should be addressed. E-mail: [email protected]
Received 20 January 2014; Revised 10 March 2014; Accepted 14 March 2014
Abstract
Crop species with the C4 photosynthetic pathway are generally characterized by high productivity, especially in environmental conditions favouring photorespiration. In comparison with the ancestral C3 pathway, the biochemical and
anatomical modifications of the C4 pathway allow spatial separation of primary carbon acquisition in mesophyll cells and
subsequent assimilation in bundle-sheath cells. The CO2-concentrating C4 cycle has to operate in close coordination
with CO2 reduction via the Calvin–Benson–Bassham (CBB) cycle in order to keep the C4 pathway energetically efficient.
The gradient in CO2 concentration between bundle-sheath and mesophyll cells facilitates diffusive leakage of CO2. This
rate of bundle-sheath CO2 leakage relative to the rate of phosphoenolpyruvate carboxylation (termed leakiness) has
been used to probe the balance between C4 carbon acquisition and subsequent reduction as a result of environmental
perturbations. When doing so, the correct choice of equations to derive leakiness from stable carbon isotope discrimination (Δ13C) during gas exchange is critical to avoid biased results. Leakiness responses to photon flux density, either
short-term (during measurements) or long-term (during growth and development), can have important implications for C4
performance in understorey light conditions. However, recent reports show leakiness to be subject to considerable acclimation. Additionally, the recent discovery of two decarboxylating C4 cycles operating in parallel in Zea mays suggests
that flexibility in the transported C4 acid and associated decarboxylase could also aid in maintaining C4/CBB balance in a
changing environment. In this paper, we review improvements in methodology to estimate leakiness, synthesize reports
on bundle-sheath leakiness, discuss different interpretations, and highlight areas where future research is necessary.
Key words: Bundle-sheath conductance, carbon isotope discrimination, CO2 concentrating mechanism, C4 photosynthesis,
leakiness.
Introduction
Plants with C4 photosynthesis often exhibit high rates of CO2
assimilation, and in particular C4 monocots such as maize,
sorghum, millet, and sugarcane are among the most productive agricultural crops in the world. The high productivity of
crops with the C4 carbon-concentrating mechanism is achieved
by improving the operating efficiency of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), the primary
carboxylating enzyme in the Calvin–Benson–Bassham (CBB)
cycle, by maximizing carboxylation relative to the competing reaction, oxygenation of ribulose bisphosphate (RuBP).
One of the oxygenation products, phosphoglycolate, is metabolically of limited use and is toxic if allowed to accumulate
(Husic et al., 1987). Conversion of phosphoglycolate to less
harmful compounds is therefore necessary but takes place at
Abbreviations: CA, carbonic anhydrase; CBB, Calvin–Benson–Bassham; ME, malic enzyme; PEP, phosphoenolpyruvate; PEPC, phosphoenolpyruvate carboxylase;
PEPCK, phosphoenolpyruvate carboxykinase; PFD, photon flux density; PSII, photosystem II; Rubisco, ribulose-1,5-bisphosphate carboxylase/oxygenase; RuBP,
ribulose bisphosphate.
© The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved.
For permissions, please email: [email protected]
3444 | Kromdijk et al.
the expense of ATP and reductant via linked metabolic processes divided between chloroplasts, peroxisomes, and mitochondria (collectively termed photorespiration). Suppression
of RuBP oxygenation leads to higher rates of net CO2 assimilation, especially in environmental conditions that limit CO2
availability (e.g. drought and high temperatures).
The C4 pathway is characterized by the spatial separation
of acquisition and reduction of inorganic carbon. C4 plants
have dimorphic chloroplasts, and Rubisco is expressed specifically in chloroplasts that are spatially distant (typically in
bundle-sheath cell chloroplasts, in species exhibiting ‘Kranz’
anatomy) from the entry point of CO2 into the leaf. The
compartmentalized Rubisco is supplied CO2 by phosphoenolpyruvate (PEP) carboxylase (PEPC) in the cytosol of
mesophyll cells, which binds inorganic carbon (bicarbonate,
HCO3– ) via the carboxylation of PEP to form C4 acids. The
C4 acids are transferred and subsequently decarboxylated at
(or close to) the site of Rubisco expression. This raises the
ratio of CO2:O2 partial pressure around Rubisco, leading to
the competitive inhibition of RuBP oxygenation.
The feasibility of C4 photosynthesis depends on the ability to
concentrate CO2 around Rubisco in an energy-efficient manner.
Regeneration of 1 mol of PEP requires the dephosphorylation
of 1 mole of ATP to AMP. Therefore, for C4 photosynthesis
to be energetically efficient, the CO2 concentrating mechanism
needs to be carefully tuned to the rate of carbon reduction by
the CBB cycle. Because of the need for diffusive exchange of
C4 cycle metabolites and CBB assimilates between bundlesheath and mesophyll cells, and the need for oxygen efflux from
bundle-sheath cells, there is a high level of connectivity via specific transporters (Bräutigam et al., 2008) and plasmodesmata
(Weiner et al., 1988; Botha, 1992; Sowinski et al., 2008). The
C4 cycle is prone to leakiness as some of the concentrated CO2
retrodiffuses from the site of C4 acid decarboxylation. This CO2
leakage is constrained by the resistance of the diffusion pathway, which can be increased by cell-wall suberization and subcellular proximal positioning of organelles, which can also help
to recapture CO2 (von Caemmerer and Furbank, 2003).
Models of the C4 cycle (Farquhar, 1983; von Caemmerer,
2000) define ‘leakiness’ as a specific term (ϕ) relating the rate of
CO2 retrodiffusion relative to rate of PEP carboxylation (Vp),
controlled by the specific bundle-sheath conductance (gbs) and
C4/CBB cycle capacity. Leakiness cannot be avoided as the C4
cycle needs to concentrate CO2 within the bundle sheath to
suppress photorespiration (Ubierna et al., 2011). To compensate for leakiness, some degree of C4 overcycling is therefore
essential, relative to CBB activity (von Caemmerer, 2000).
Originally, leakiness was used to define the operating efficiency of the C4 pathway. Values of leakiness inferred from
organic material carbon isotope composition varied around
20–30% (Farquhar, 1983) and related to bundle-sheath anatomy
in the varying decarboxylase subgroups in grasses (Hattersley,
1982). With the development of instantaneous carbon isotope
discrimination measurement systems, leakiness could be shown
to be relatively constant under a wide range of conditions but to
increase under limiting light (Evans et al., 1986). Recently, there
has been increasing interest in providing a more mechanistic analysis of leakiness (von Caemmerer and Furbank, 2003;
Cousins et al., 2006a, 2008; Kromdijk et al., 2010; Ubierna
et al., 2011, 2013; Bellasio and Griffiths, 2013, 2014a, b), demonstrating that C4 leaves can poise C4 and CBB processes to
reduce leakiness when leaves are adapted to low light (Bellasio
and Griffiths, 2013, 2014b). The aim of this review is to consider
these developments and their associated approaches, and also
assess the relevance of leakiness for a number of diverse issues
in C4 biology. These key areas are as follows:
1. The significant research effort dedicated towards engineering a C4 pathway into a C3 staple crop such as indica rice
(Oryza sativa). The challenges and bottlenecks that are
associated with such development have been extensively
reviewed (Kajala et al., 2011; Covshoff and Hibberd,
2012; Driever and Kromdijk, 2013; see also other papers in
this issue) and relate to the need to introduce appropriate
structural changes and tissue-specific enzyme expression.
When this research results in any improved target variety,
it is important that we can assess the coupling of C4 and
CBB metabolic processes and model the underlying processes to inform subsequent research directions.
2. The need to understand the metabolic and environmental
plasticity in C4 systems. The distinction between C4 subgroups, based on associated decarboxylase pathways, has
increasingly been shown to be insufficient (Furbank, 2011;
Pick et al., 2011), due to co-existence of multiple decarboxylating pathways within the same C4 species. It was
also initially thought that relatively fixed energetic partitioning between C4 and CBB carboxylase systems (von
Caemmerer, 2000) could constrain acclimation to changing light intensities (Evans et al., 2007). We now recognize that these views are too rigid and that the flexibility
in biochemistry reflects plasticity under contrasting light
regimes (Bellasio and Griffiths, 2014a), as well as metabolic robustness (Pick et al., 2011; Stitt and Zhu, 2014).
3.Recognition of the importance of constant adaptation of
leaves to the prevailing light environment. In crop canopies,
leaves initially expand and acclimate under fully exposed
conditions, and then become progressively overtopped and
shaded by the developing canopy. Leakiness has been suggested previously to lead to significant losses of productivity
in C4 crop canopies (Kromdijk et al., 2008). However, these
findings could overestimate the leakiness-associated loss in
photosynthetic efficiency. Leakiness increases at low photon
flux density (PFD) could be overstated due to improper use
of simplifications in the calculations (Ubierna et al., 2011,
2013). Recent results also show that leakiness and C4 operating efficiency at limiting light intensity could be less tightly
connected than previously thought (Bellasio and Griffiths,
2013, 2014b). Additionally, acclimation of leakiness to
growth under low light intensity has been shown to exist
(Tazoe et al., 2008; Kromdijk et al., 2010; Pengelly et al.,
2010; Bellasio and Griffiths, 2013, 2014b). Canopy architecture (Murchie et al., 2009) as well as the extent that mature
leaves acclimate to understorey conditions are key traits that
might reduce losses in carbon gain due to leakiness.
Therefore, an understanding of the regulation between CBB and
C4 processes and how low leakiness is achieved are of considerable
Bundle-sheath leakiness in C4 photosynthesis | 3445
relevance. In this paper, we will review and synthesize advances
with regard to methodology to determine C4 bundle-sheath
leakiness, phenomenological findings of leakiness, the balancing
of CBB/C4 processes, and parallel operation of multiple decarboxylating biochemical pathways within leaves of Zea mays. The
discussion of leakiness has been organized to reflect the changes
in the light environment experienced by a typical C4 leaf during
growth and development: light intensity (short and long term),
spectral composition, and the occurrence of fluctuations in intensity. Finally, we also highlight areas for future research.
Methods to measure leakiness and
associated issues
Leakiness cannot be measured directly and therefore it has to
be estimated using indirect methods. These methods can be
grouped into three categories: (i) radiolabelling (Furbank and
Hatch, 1987; Hatch et al., 1995); (ii) quantum yield (Farquhar,
1983; Furbank et al., 1990); and (iii) carbon isotope discrimination (Farquhar, 1983; Evans et al., 1986). Each of these methods has assumptions and shortcomings that produce variable
results for leakiness. Nevertheless, all methods overlap in leakiness values of 0.2–0.3 for most species under regular ambient
conditions. Leakiness values derived with radiolabelling methods were 0.08–0.29 (Furbank and Hatch, 1987; Hatch et al.,
1995; Jenkins, 1997; von Caemmerer and Furbank, 2003).
Estimations of leakiness from quantum yield ranged from 0.04
to 0.70 (Ehleringer and Pearcy, 1983; Farquhar, 1983). Values
of leakiness via the carbon isotope discrimination were around
0.2–0.3 (Henderson et al., 1992; Ubierna et al., 2011, 2013).
The variation among the different methods can be attributed
to their imbedded assumptions, which include assuming the
sizes of different cellular compartments (in radiolabelling techniques), several assumptions regarding the energy production
and requirement of C4 photosynthesis (in quantum yield and
carbon isotope discrimination methods), values for unknown
fractionation factors (in carbon isotope discrimination), and
assumptions regarding bundle-sheath resistance values (in
radiolabelling and carbon isotope methods).
Nevertheless, method (iii) is most commonly used, especially with the recent development of laser technologies that
have greatly facilitated the measurement of leaf CO2 isotope
exchange. Therefore, we will briefly review methods (i) and
(ii) but will cover method (iii) in more detail. For comparison,
representative leakiness values obtained with each method
are shown in Table 1.
Radiolabelling
Two radioisotope methods have been used to quantify either
the size of the inorganic carbon pool in the bundle-sheath
cells (Furbank and Hatch, 1987) or the leakage rate of CO2
out of the bundle-sheath cells (Hatch et al., 1995). In brief,
Table 1. Selection of leakiness values measured with different methods
Simplifications for Δ13C– online calculations: (1) negligible ternary effects (t=0); (2) CO2 is in equilibrium with HCO3– in the mesophyll cytoplasm
(b4c=b4); (3) negligible fractionation during photorespiration and dark respiration (b3=b3′=30‰, b4 =b4′=–5.7‰); (4) mesophyll conductance
(gm) is infinite (Ci=Cm); (5) boundary layer conductance is infinite (Ca=CL), and (6) CO2 inside the bundle-sheath cells is much larger than in
the mesophyll cells [Cbs/(Cbs–Cm)≈1 and Cm/(Cbs–Cm)≈0]. The range of values for a given condition and reference represents results for plants
measured under different [O2] or grown under different light environments. Photosynthetically active radiation (PAR) units are µmol m–2 s–1.
Method
Species type
Radiolabelling-inorganic C pool
All
Radiolabelling-leak rate
Monocots
NAD-ME dicots
NADP-ME dicots
NADP-ME monocots
PCK monocots
NADP-ME dicots
NAD-ME monocot
NAD-ME dicots
All
Quantum yield
Δ13C – dry matter
Δ13C – online
Monocots
Dicots
NADP-ME grasses
NAD-ME grasses
Leakiness (ϕ)
0.15
0.08–0.14
0.08–0.12
0.20–0.29
–0.03–0.54
0.04–0.55
0.14–0.60
0.17–0.61
0.37–0.70
0.30–0.50
0.21–0.30
0.21
0.3 @ PAR=2000; 0.6 @ PAR=150
0.20 @ PAR=2000; 0.35–0.48 @ PAR=125
0.18 @ PAR=750; 0.24 @ PAR=125
0.13–0.34 @ PAR=2000
0.20 @ PAR=1000; 0.45 to 0.90 @ PAR=50
0.19 @ PAR=2000; 0.21 @ PAR=150
0.20 @ PAR=500; 0.20 to 0.50 @ PAR=30
0.21–0.29 @ PAR=2000
Reference
Simplifications
Jenkins et al. (1989); von
Caemmerer and Furbank (2003)
Hatch et al. (1995)
Farquhar (1983)
Farquhar (1983); Henderson et al.
(1992); Kubásek et al. (2007)
Henderson et al. (1992)
Henderson et al. (1992)
Cousins et al. (2006a)
Pengelly et al. (2010)
Ubierna et al. (2011)
Cousins et al. (2008)
Kromdijk et al. (2010)
Ubierna et al. (2013)
Bellasio and Griffiths (2013)
Cousins et al. (2008)
(1) (4) (5) (6)
(1) (2) (5) (6)
(1) (2) (4) (5)
(1) (3) (4) (5) (6)
(1) (5)
(2) (4)
(2) (5)
(1) (3) (4) (5) (6)
3446 | Kromdijk et al.
the Furbank and Hatch (1987) method consisted of placing
a leaf in a clear illuminated chamber that was injected with
14
CO2. After a period of time, the leaves were quenched with
liquid nitrogen and the radiolabelled acid-labile carbon pool
in the leaf was measured to compute the concentration of
CO2 plus HCO3– in the bundle-sheath cells, using assumptions
for volumes of bundle-sheath cells, cytosol, and chloroplast.
Estimations of the bundle-sheath leakage resistance (rbs) can be
obtained from radiolabelling or CO2 uptake of PEPC-inhibited
leaves (Furbank et al., 1989; Jenkins et al., 1989; Brown, 1997;
Kiirats et al., 2002) or direct diffusion measurements on the
Amaranthus edulis PEPC mutant (Kiirats et al., 2002). Finally,
when these estimates for rbs and the estimates by Furbank and
Hatch (1987) for the leaf inorganic carbon pool are used in a
model for the inorganic carbon composition within the bundlesheath cells, leakiness values can be computed (Jenkins, 1997;
von Caemmerer and Furbank, 2003). Alternatively, Hatch
et al. (1995) estimated the leak rate directly instead of estimating it from the size of the bundle-sheath inorganic carbon pool.
These experiments labelled leaves with 14CO2 during steadystate photosynthesis and subsequently transferred them to a
‘chase’ chamber after which the time course of 14CO2 release
was measured. Leakage was then calculated by comparing the
rates of net CO2 assimilation and 14CO2 release, correcting for
the minor portion of refixed 14CO2.
Radioisotope methods have not been widely used because
they involve difficult experimental set-ups, complex calculations, and several assumptions. The calculation of the size of
the inorganic C pool by Furbank and Hatch (1987) makes several assumptions regarding the volume of bundle-sheath cells,
cytosol, and chloroplasts. Subsequently, a leakage rate could
only be derived once bundle-sheath resistance was known and
the result was very sensitive to values chosen for this parameter. For example, the leak rate was estimated to be 11% of
the CO2 originally released in the bundle-sheath cells, but this
value varied from 19 to 5% when the bundle-sheath resistance was halved or doubled (Furbank and Hatch, 1987). The
method used by Hatch et al. (1995) is undoubtedly more direct
and elegant but still requires a complex set-up. For example, it
requires time-course measurements of 14CO2 released, which
is not feasible in many laboratories. Additionally, the main
criticism of this technique is that refixation of 14CO2 could be
underestimated (von Caemmerer and Furbank, 2003).
Quantum yield
Leakiness can also be estimated by comparing measurements
and theoretical estimations of quantum yield of CO2 fixation. With this method, several assumptions need to be made
regarding the energy requirement of C4 photosynthesis, the
end products of photosynthesis, spectral differences in quantum requirements, and the proportion of absorbed quanta that
are used for processes other than photosynthesis (Furbank
et al., 1990). Additional assumptions include complete suppression of photorespiration and a rigid ATP/NADPH stoichiometry, whereas shifting requirements for ATP and NADPH
between bundle-sheath and mesophyll cells are not considered.
Unavoidably, derivations of leakiness from quantum yield
are affected by all these uncertainties and assumptions. There
also appears to be a discrepancy between the quantum yield
method and the isotope methods, leading to poor correlation
between leakiness estimates from both methods (Hatch et al.,
1995; von Caemmerer and Furbank, 2003).
Stable carbon isotope discrimination (Δ13C)
This method is based on comparing theoretical models of
Δ13C in C4 plants (Farquhar, 1983; Farquhar and Cernusak,
2012) with measured Δ13C (Evans et al., 1986; von Caemmerer
et al., 1997). Details regarding measurements of Δ13C are presented in Appendix 1. Below, we discuss the post-hoc modelling required to interpret measured Δ13C to derive leakiness.
Models for Δ13C during C4 photosynthesis combine a series
of kinetic and equilibrium fractionations, weighted by the proportional CO2 drawdown at each step. Fractionation associated with Rubisco-mediated carboxylation (27–30‰; Roeske
and O’Leary, 1984; Cernusak et al., 2013) is approximately
one order of magnitude higher than Δ13C in C4 plants (2–6‰),
where a low fractionation expressed by PEPC is tempered by
diffusion limitation through stomata, dissolution, and conversion to HCO3– substrate. Within the C4 bundle sheath, the
extent that Rubisco fractionation is expressed is determined
by the proportional leakage flux, leading to the correlation
between leakiness with δ13C of organic material, and with
Δ13C expressed in real time during C4 gas exchange (Farquhar,
1983; von Caemmerer, 2000). The theoretical model for C4
Δ13C (see Eq. 7b in Farquhar, 1983) was recently updated to
include ternary effects (Eq. 19 in Farquhar and Cernusak,
2012), which correct for the interaction between opposing
fluxes (CO2, H2O) following the same diffusional trajectory:
∆=
1  Ca − C L
C −Ci 

ab
+ as L
1 − t 
Ca
Ca 



 bC


b4 + φ 3 bs − s
Cbs − Cm
 Cm 
1 + t 
Ci − Cm

+
+
(es + al )
φC m
Ca 
1 − t 
Ca
1+


Cbs − Cm


(Eq. 1)
where
b3 = b3′ −
and
eRLIGHT fF −
Vc
Vc
(Eq. 2)
eRm Vp
(Eq. 3)
b4 = b4′ −
The other variable definitions and values are provided in
Table 2.
Leakiness (ϕ in Eq. 1) is defined as the diffusion-driven
bundle-sheath CO2 leak rate relative to the rate of PEP
carboxylation:
φ=
gbs (Cbs − Cm )
Vp
(Eq. 4)
Bundle-sheath leakiness in C4 photosynthesis | 3447
Table 2. Variable definitions in the Δ13C model
Symbol
Definition
Values/units
A
Leaf photosynthetic rate
ab
as
al
13
µmol m–2 s–1
2.8 per mil
4.4‰
0.7‰
(Farquhar and Cernusak,
2012)
αac
C fractionation due to diffusion of CO2 across the boundary layer
13
C fractionation due to diffusion of CO2 in air (Craig, 1953)
13
C fractionation during diffusion of CO2 through water (O’Leary, 1984)
Fractionation factor for the isotopologues of CO2 diffusing in air that equals
α ac = 1+ a = 1+
ab ( Ca − CL ) + as ( CL − Ci )
Ca − Ci
13
C fractionation during carboxylation by Rubisco including respiration and
photorespiration fractionations, Eq. 2 (Farquhar, 1983)
13
C fractionation during carboxylations by Rubisco
(Roeske and O’Leary, 1984)
Net fractionation by CO2 dissolution, hydration and PEPc including
respiratory fractionation, Eq. 3 (Farquhar, 1983)
Net fractionation by CO2 dissolution, hydration and PEPc including respiratory
 Vp 
 Vp  eR
fractionation and CA (Farquhar, 1983): b4 c = b4′  1 −  + ( es + h)   − m
 Vh 
 Vh 
Vp
‰
–5.7‰ at 25 °C, but
variable with temperature
Ca
Net fractionation by CO2 dissolution, hydration and
PEPc activity (Farquhar, 1983)
CO2 mole fraction in the atmosphere
Ci
CO2 mole fraction in the leaf intercellular spaces
µmol mol–1
Cl
CO2 mole fraction at the leaf surface
µmol mol–1
Cm
CO2 mole fraction in the mesophyll cells
µmol mol–1
Cbs
CO2 mole fraction in the bundle-sheath cells
µmol mol–1
‰
b3
b3’
b4
b4c
b4’ .
30‰
‰
‰
µmol mol–1
13
Δ C
Photosynthetic discrimination against
Δobs
Observed 13C photosynthetic discrimination
‰
δ13Cx
E
e
Carbon isotope composition (Rx/Rstd(−1))×1000
‰
Transpiration rate
13
C fractionation during decarboxylation (Ghashghaie et al., 2001;
Hymus et al., 2005; Barbour et al., 2007)
13
C fractionation during decarboxylation including measurements
artefacts, Eq. 5 (Wingate et al., 2007; Cernusak et al., 2013)
13
C fractionation during internal CO2 dissolution
(Mook et al., 1974; Vogel, 1980)
13
C fractionation during photorespiration (Evans and Von Caemmerer, 2013;
Rooney, 1988; von Caemmerer and Evans, 1991; Gillon and Griffiths, 1997;
Scartazza et al., 1998; Lanigan et al., 2008)
Photorespiratory rate (F=0.5Vo)
mmol m–2 s–1
0 to –10‰
13
e′
es
f
F
C
‰
1.1‰
0 to 16‰
µmol m–2 s–1
mol m–2 s–1
mol m–2 s–1
Unitless
JATP
Combined boundary layer and stomatal conductance to CO2
Boundary layer conductance to CO2
Leakiness: proportion of carbon fixed by PEPc that
leaks out of the bundle-sheath cells (Farquhar, 1983)
Mesophyll (transfer or internal) conductance to CO2
Bundle-sheath conductance to CO2
Catalysed fractionation during CO2 hydration (Cousins et al., 2006a)
Modelled ATP production rate (Eq. 9 in Bellasio and
Griffiths, 2013; Eq. 3 in Ubierna et al., 2013).
ATP production rate (Eq. 2 in Bellasio and Griffiths, 2013)
RLIGHT
Total non-photorespiratory CO2 production in the light
µmol m–2 s–1
Rm
Mesophyll non-photorespiratory CO2 production
in the light (=0.5RLIGHT) (von Caemmerer 2000)
Fractionation during leakage of CO2 out of
the bundle-sheath cells (Henderson et al., 1992)
µmol m–2 s–1
gac
gb
ɸ
gm
gbs
h
JMOD
s
t
Vc
Ternary effects (Eq. 7 in Farquhar and Cernusak, 2012) t =
Rubisco carboxylation rate
mol m–2 s–1 bar–1
mol m–2 s–1
1.1‰
µmol electrons m–2 s–1
µmol electrons m–2 s–1
1.8‰
α ac E
2 gac
Unitless
µmol m–2 s–1
Vh
CO2 hydration rate
µmol m–2 s–1
Vo
Rubisco oxygenation rate
µmol m–2 s–1
Vp
PEP carboxylation rate
µmol m–2 s–1
3448 | Kromdijk et al.
and can be solved from Eq. 1. Because the complexity of this
equation, it is tempting and often valid to use a simplified
form. These simplifications can be achieved by a number of
key assumptions; however, it is critical to evaluate the validity of these assumptions before applying a simplified equation as a substitute for Eq. 1. As an example, the check-list
shown in Fig. 1 identifies the most parsimonious yet suitable
equations for modelling Δ13C under particular measurement
conditions.
Many parameters in the Δ13C model are known constants
(see Table 2) or can be derived from gas exchange. However,
the fractionation factors b3 and b4 (and parameters therein),
bundle-sheath conductance gbs and bundle-sheath CO2 concentration Cbs are particularly difficult to constrain experimentally but can be approximated using mathematical
modelling. Recently, two approaches have been used to estimate Cbs and gbs: the Δ/Δ method (Kromdijk et al., 2010;
Ubierna et al., 2013) and the J/J method (Bellasio and
Griffiths, 2013). The Δ/Δ method consists of comparing
measurements and models of Δ13C and adjusting gbs until
model and measurements match. In the J/J method, a theoretical total electron transport rate J (JMOD) is calculated by
rearranging von Caemmerer (2000) C4-light limited model
(see Eq. 3 in Ubierna et al., 2013). JMOD is then compared
with chlorophyll fluorescence estimated J (JATP) and gbs is
tuned until both values match. Obtaining values for JATP
from a theoretical relationship between quantum yield of
photosystem II (PSII) and ATP production rate requires
parameter inputs that are difficult to measure or unknown
(von Caemmerer, 2000). Alternatively, JATP can be calibrated
Fig. 1. Decision tree for use of simplifications in the calculation of leakiness from Δ13C. For explanation of symbols, see Table 2.
Bundle-sheath leakiness in C4 photosynthesis | 3449
empirically at low O2 and the value can then be corrected
for the small ATP demand for photorespiration (Yin and
Struik, 2009; Yin et al., 2011b; Bellasio and Griffiths, 2013).
Both approaches have some degree of circularity as they
derive both gbs and Cbs from the same dataset. To overcome
this problem, Bellasio and Griffiths (2013) have recently
used the J/J method together with the Δ/Δ method to simultaneously get two sets of estimates for gbs and Cbs using gas
exchange and chlorophyll fluorescence together with online
Δ13C. Estimations of gbs with the J/J method (0.82 × 10–3–
1.03 × 10–3 mol m–2 s–1) were lower than with the Δ/Δ method
(1.27 × 10–3–4.64 × 10–3 mol m–2 s–1) (Bellasio and Griffiths,
2013). The corresponding estimates for Cbs varied with light
intensity but were consistently higher in the J/J method. The
reasons behind these differences are currently unresolved,
but uncertainties related to both methods are quite substantial. The Δ/Δ method requires the validity of a range
of assumptions as well as measurement or estimation of
a range of variables as outlined in this paragraph. The J/J
method carries fewer assumptions but critically requires the
quantum yield of ATP production to follow the same correlation with the estimation of PSII efficiency under contrasting (2 and 21%) ambient O2 concentrations. This is further
complicated due to the unknown mitochondrial contribution to ATP supply for the C4 pathway and the dimorphic
nature of C4 chloroplasts, which means that the chlorophyll
fluorescence-derived estimate of PSII efficiency in C4 leaves
represents an unknown contribution from mesophyll versus
bundle-sheath chloroplasts. Therefore, both state-of-theart methods have a number of associated problems, which
decrease the precision and accuracy to estimate gbs and Cbs.
However, ignoring these variables for estimates of leakiness
at low PFD would probably result in larger errors (Ubierna
et al., 2011).
Once values for gbs and Cbs have been derived, the fluxes
Vc, Vp, and F can be computed with a C4 biochemical model
(e.g. von Caemmerer, 2000). Rm (part of RLIGHT that originates from mesophyll cells) is computed as a fixed fraction of
RLIGHT (mitochondrial CO2 release during illumination not
associated with photorespiration), which is often assumed to
approximate measured rates of CO2 release in darkness (e.g.
Kromdijk et al., 2010; Ubierna et al., 2013). This probably
misrepresents the actual respiration rate in the light (Tcherkez
et al., 2008), and for detailed work, it might be preferable to
use more complex but accurate techniques such as combined
measurements of chlorophyll fluorescence and gas exchange
(Yin et al., 2011a; Bellasio and Griffiths, 2013; for a sensitivity analysis, see Bellasio and Griffiths, 2014b).
Estimates for fractionation during photorespiration (f)
and respiratory fractionation e also suffer from uncertainties,
ranging from 0 to 16‰ and 0 to –10‰, respectively (Rooney,
1988; von Caemmerer and Evans, 1991; Gillon and Griffiths,
1997; Scartazza et al., 1998; Ghashghaie et al., 2001; Barbour
et al., 2007; Bathellier et al., 2008; Lanigan et al., 2008;
Tcherkez et al., 2008, 2011; Evans and von Caemmerer, 2013).
An apparent respiratory fractionation can occur if the δ13C
of the atmosphere where the measurements are conducted
(δmeasurements) differs from that of the ambient air where plants
grew (δgrowth). In this case, e is substituted by (Cernusak et al.,
2013):
e ′ = e + δ measurements – ∆ obs – δ substrate (Eq. 5)
δsubstrate is the isotopic composition of the substrate for respiration, and its value depends on whether this substrate
derives from assimilates metabolized during or before the
measurement. Additional assumptions are needed for the
expression of b4. Generally, carbonic anhydrase (CA) activity
is supposed to be sufficient to warrant full CO2 and HCO3–
isotopic equilibrium. If not, the term b4 should be replaced by
the expression given by Farquhar (1983: see Table 2). CA has
been shown to be in excess in Flaveria bidentis (Cousins et al.,
2006a, b) but to have lower contents in C4 monocots (Gillon
and Yakir, 2001) and C4 grasses (Cousins et al., 2008), which
means justification of this assumption is likely to be species
dependent.
Based on this summary of the issues related to determining leakiness, it becomes obvious that it is not trivial to estimate leakiness based on any of the presented methods. We
intend Fig. 1 to be of help to choose the correct form for Eq.
1, but leakiness often cannot be determined without having
to measure or estimate a range of difficult-to-measure variables, as well as underpin the validity of a number of key
assumptions.
Leakiness as a function of growth or
measurement conditions
Although leakiness appears to be remarkably constant over
a wide range of environmental conditions (e.g. Henderson
et al., 1992; Cernusak et al., 2013), the largest fluctuations have been reported for short-term measurements of
leakiness at contrasting light intensities (e.g. Cousins et al.,
2006a, 2008; Tazoe et al., 2006, 2008; Kromdijk et al., 2010).
Consequentially, most reports in the last decade have focused
on the (low) light response of bundle-sheath leakiness. In the
following paragraphs, we will separate the response of leakiness to light into different components. We will first review
the response of leakiness to short-term changes in PFD, followed by responses to short-term changes in the spectral composition of incident irradiance and long-term acclimation to
the light environment under controlled and field conditions.
Finally, we discuss the uncertainties associated with ATP supply and demand, which are critical to assess implications of
leakiness for C4 photosynthetic quantum yield.
Is leakiness responsive to short-term changes in PFD?
Leakiness is often estimated by means of the isotope method,
where Δ13C is measured and subsequently leakiness is calculated by comparing these measurements with a mathematical
formulation of Δ13C. The vast majority of studies consistently
report increased Δ13C with decreased irradiance during measurements (Cousins et al., 2006a, 2008; Kubásek et al., 2007;
Tazoe et al., 2008; Kromdijk et al., 2010; Pengelly et al., 2010;
3450 | Kromdijk et al.
Ubierna et al., 2013) and only in Boerhavia coccinea Mill. and
Sorghum nigrum could no significant effect of light intensity
on Δ13C be found (Kubásek et al., 2007), although ‘low’ PFD
in this study was considerably higher than in most other studies (300 µmol m–2 s–1). However, these studies differ in the way
leakiness is computed from Δ13C. When simplifications were
applied in Eq. 1 to compute leakiness, most studies concluded
that there was a large bundle-sheath leakiness increase at low
PFD (Cousins et al., 2006a; Tazoe et al., 2008; Kubásek et al.,
2007; Cousins et al., 2008; Pengelly et al., 2010). However,
when subsequent studies used less profound simplifications
in the computation of leakiness from Eq. 1, increases in Δ13C
at low light translated into insignificant (Ubierna et al., 2013)
or moderate (Kromdijk et al., 2010; Bellasio and Griffiths,
2013, 2014b) increases in leakiness. Larger values of leakiness
only occurred at very low PFD (≤100 µmol m–2 s–1), when the
measurement error associated with Δ13C increases substantially (Kromdijk et al., 2010; Bellasio and Griffiths, 2013).
A similar pattern in the light response of leakiness was also
found by Yin et al. (2011b) using a different method based
on combined measurements of gas exchange and chlorophyll
fluorescence. In this report, leakiness was relatively constant
over a wide range of PFD, and high values were found exclusively at very low PFD.
Similar to ‘Kranz’ C4 species, the light response of Δ13C
for two single-celled C4 species (Bienertia sinuspersici and
Suaeda aralocaspica) showed a pronounced increase at low
PFD (King et al., 2012). These values translated into an
increase in leakiness at low PFD, although recent findings by
the same group (Stutz et al., 2013) indicated that the difference between δ13C of CO2 during growth and during measurements may have led to underestimation of the isotopic
signature of RLIGHT, leading to overestimation of leakiness in
the work by King et al. (2012). RLIGHT can have a profound
influence on leakiness at very low PFD (Kromdijk et al.,
2010; Bellasio and Griffiths, 2013). However, to include more
elaborate corrections for this variable requires not only the
substrate of respiratory CO2 to be known but also the magnitude of RLIGHT, which remains tricky to estimate (Bellasio
and Griffiths, 2013).
Effects of spectral composition of irradiance on
leakiness and CBB/C4 balance
Evans et al. (2008) reported that (short-term) changes in the
spectral composition of incident irradiance while keeping the
PFD constant (at 350 µmol m–2 s–1) severely influenced the
efficiency of gas exchange in Flaveria bidentis. In particular,
they found that wavelengths between 400 and 500 nm (blue)
decreased the rate of net gas exchange. This was explained in
terms of changes in the excitation balance between the two subpopulations of chloroplasts (mesophyll and bundle sheath),
which resulted in reduced supply of ATP in bundle-sheath
chloroplasts. Sun et al. (2012) expanded the work by Evans
and colleagues by performing measurements of Δ13C online
with gas exchange at different spectral compositions of incident irradiance (peak wavelengths of 635, 522, and 460 nm).
They found that the shortest wavelength (460 nm) diminished
the quantum use efficiency of photosynthetic gas exchange
but had no effect on leakiness computed from Δ13C values.
Bellasio and Griffiths (2014a) confirmed the insensitivity of
leakiness to short-term spectral changes in maize. Absorption
of lower wavelengths (<500 nm) by non-photosynthetic pigments was shown to significantly influence the quantum use
efficiency in C3 photosynthesis (McCree, 1972; Hogewoning
et al., 2012) and may also play a role in explaining spectral
effects on C4 gas exchange. Under transient changes between
red, green, and blue light, Sun et al. (2014) reported in Z. mays
and Miscanthus×giganteus that rates of net CO2 assimilation
(Anet) responded quickly to changes in light quality with lowest rates of Anet under blue light compared with other light
treatments. Interestingly, under these conditions, there was a
species-dependent difference in the response of leakiness with
a relatively large change in Miscanthus×giganteus but not in
Z. mays. However, in both species, given enough time, leakiness returned to a constant value, suggesting a rebalancing
and coordination of the C4 and C3 cycles.
Light environment during growth and development:
controlled versus field conditions
Although changes in PFD during measurements have often
resulted in increased Δ13C at low PFD, the response to light
intensity during growth does not follow the same pattern.
For example, Tazoe et al. (2008) reported lower leakiness
when Amaranthus cruentus was grown at lower PFD. Similar
observations were reported for Z. mays (Kromdijk et al.,
2010; Bellasio and Griffiths, 2013) and F. bidentis (Pengelly
et al., 2010). Even when Z. mays was grown at extremely low
PFD (100 µmol m–2 s–1), leakiness still decreased (Bellasio
and Griffiths, 2013). This acclimation response was observed
consistently, even when leaves were first fully developed at
600 µmol m–2 s–1 and then subjected to low-light conditions for
several weeks (Bellasio and Griffiths, 2014b). Acclimation of
leakiness to PFD could arise from biochemical adjustment, as
well as from changes in bundle-sheath conductance, which was
also reported to decrease with decreasing PFD during growth
(Kromdijk et al., 2010; Bellasio and Griffiths, 2013). Bellasio
and Griffiths (2013) suggested that regulation of bundle-sheath
conductance as a function of short-term changes in PFD could
explain the leakiness response found in low PFD grown plants.
Ultrastructure analyses by Bilska and Sowinski (2010) showed
that rapid plasmodesmatal closure at low temperature can limit
the transport of photosynthetic intermediates. Whether this
mechanism is also influenced by PFD is unclear.
Acclimation to a dynamic light environment can also
affect Δ13C and leakiness. For example, Kubásek et al. (2013)
reported that acclimation to a bimodal light regime (alternating between a PFD of 95 and 950 µmol m–2 s–1 with intervals of 1 to 30 min) compared with acclimation to constant
light with the same daily integral caused a decrease in specific leaf area and an increase in leakiness in Amaranthus
caudatus and Setaria macrostachya (estimated from biomass
δ13C, corrected for post-photosynthetic fractionation). The
bimodal light pattern also negatively affected photosynthesis and growth of both species, which was explained mainly
Bundle-sheath leakiness in C4 photosynthesis | 3451
by the hyperbolic shape of the photosynthetic light response.
However, Kubásek and colleagues also attributed the lower
efficiency of the C4 species relative to C3 under dynamic
light to inefficiencies during readjustment of photosynthetic
induction. It is unclear how generic these results are, as previous work indicated that no clear differences exist between C3
and C4 in lightfleck utilization (Pearcy and Calkin, 1983; Sage
and Pearcy, 2000). Maximum quantum yield of CO2 fixation
decreased due to varying light intensity in Amaranthus caudatus but not in Setaria macrostachya (Kubásek et al., 2013).
This shows that some aspects of acclimation of C4 photosynthesis to changes in the light environment during canopy
development are distinctly species specific.
It is uncertain which factors control the acclimation
responses to low or dynamic light and if they are the same
across species. Leaf nitrogen content may also play an important role. For example, when interactive effects between leaf
nitrogen and light intensity on leakiness were investigated,
the results were species dependent. Whereas leaf δ13C and
computed leakiness in Amaranthus cruentus (Tazoe et al.,
2006) seemed to be non-responsive to leaf nitrogen content, high leaf nitrogen increased the effects of low PFD on
leakiness in Z. mays (Yin et al., 2011b). Similarly, changes
in leaf anatomical properties were not consistent across species. Acclimation to low PFD induced higher interveinal distance in dicots Amaranthus cruentus (Tazoe et al., 2006) and
F. bidentis (Pengelly et al., 2010), whereas interveinal distance
decreased with low PFD in the monocot Z. mays (Kromdijk
et al., 2010). More studies are needed describing anatomical
and functional traits under different light environments to
separate general from species-specific acclimation responses.
When leaves in C4 canopies become progressively shaded
during development, they simultaneously experience a gradual
decrease in the daily integral of intercepted irradiance and
changes in spectral composition of intercepted irradiance, as
well as an increased exposure to sharp changes in light intensity, followed to some extent by remobilization of leaf nitrogen to higher-placed leaves (Drouet and Bonhomme, 1999).
All these interacting factors make it difficult to predict the
response of Δ13C and leakiness during leaf growth and development under field conditions. There is only one study that
has reported measurements of Δ13C under field conditions
(Kromdijk et al., 2008). This work showed an increase in Δ13C
during gas exchange with decreasing vertical leaf position
within a Miscanthus×giganteus canopy. Pignon (2013) also
showed that quantum use efficiency of Miscanthus×giganteus
leaves declined along the same vertical gradient within the canopy and that this decline was correlated primarily with decreasing PFD (and not with leaf aging). Identification of the specific
factors responsible for these acclimation effects requires more
work under field conditions on a diverse range of C4 species.
ATP supply versus demand and the quantum yield
discrepancy
The difficulty of interpreting leakiness responses and translating them into further implications for C4 carbon assimilation
arises at least partially from the uncertainties associated with
the production of ATP and the subsequent ATP use in either
the CO2-concentrating mechanism or CO2-reducing cycle.
Production of ATP is often estimated by means of fitting
a non-rectangular hyperbole to (chlorophyll fluorescencebased) estimates for linear electron transport. Although this
approach severely simplifies the complexities of the C4 system
(see discussion in Kromdijk et al., 2010), it generally simulates
C4 gas exchange accurately under a wide range of conditions.
However, to interpret leakiness values, more refined methods
are needed. Yin et al. (2011b) provided an empirical approach
to directly calibrate the fluorescence estimates on ATP supply
under non-photorespiratory conditions. Ubierna et al. (2013)
further constrained uncertainty associated with the potential
flexibility of ATP supply by comparing measurements of the
electrochromic shift (absorbance changes at 520 nm during
gas exchange) with linear electron flux (derived from fluorescence). Based on the strongly linear correlation, Ubierna
and colleagues concluded that proportional ATP supply from
bundle-sheath and mesophyll chloroplasts was probably constant over a wide range of light intensities. An additional way
to further constrain the calculation of ATP supply was presented by Yin and Struik (2012), who used the assumption
of simultaneous co-limitation of C4 photosynthesis by supply
of NADPH as well as ATP. As the NADPH demand during
C4 photosynthesis has less uncertainty associated with it than
the ATP demand, and the NADPH-limited equation shares
a number of variables with the ATP-limited equation, matching the NADPH supply and demand also reduces uncertainty
in the ATP-limited form.
With regard to the proportional demand for ATP, the commonly used model for C4 photosynthesis by von Caemmerer
(2000) uses a fixed ratio of ATP partitioning between PEP
regeneration and bundle-sheath-associated processes of 2:3.
This ratio is based on the proportional ATP demand of one
turn of the C4 cycle (2 moles of ATP per mole of regenerated
PEP) versus one turn of the CBB cycle (2 moles of ATP for
phosphorylation of 2 moles of 3-phosphoglyceric acid and
1 mole of ATP per mole regenerated RuBP). Note that this
scheme assumes that ATP demand associated with photorespiration and overcycling is negligible. However, suppression
of photorespiration in C4 species like maize is not complete
(see, for example, Zelitch et al., 2009), especially under low
irradiances. Kromdijk et al. (2010) therefore used a different partitioning approach, in which ATP from photophosphorylation was distributed optimally to achieve maximal
net assimilation rates (by analytically solving dAn/dx=0, in
which An represents net assimilation and x is the proportional
allocation of ATP to PEP regeneration). This partitioning
approach was able to reproduce the leakiness response to
PFD at differing O2 concentrations in young maize plants,
which suggested that photorespiration could be involved in
regulation of the C4 cycle, especially when plants are grown
at high light intensity. A mechanistic underpinning for this
hypothesis may have been provided recently by Bräutigam
et al. (2008) who showed that the glycerate transporter plgg1
(Pick et al., 2013; originally termed MEP1 by Bräutigam
et al., 2008) is specifically expressed in the envelope of mesophyll chloroplasts in maize. This allows for the initial build-up
3452 | Kromdijk et al.
of metabolic substrate for the triose phosphate shuttle during photosynthetic induction but would also provide a direct
influx of additional substrate into the carbon-concentrating
mechanism via phosphorylation of glycerate to 3-phosphoglyceric acid (using 1 ATP) and subsequent interconversion
to PEP, when photorespiratory phosphoglycolate production
increases.
Another factor to consider when translating leakiness
into ATP-use efficiency is the passive concentration of CO2
via respiratory CO2 release in bundle-sheath cells. This can
play a significant role when assimilation and active concentration via the C4 acid shuttle are severely limited (e.g.
at low PFD; Kromdijk et al., 2010; Bellasio and Griffiths,
2013, 2014b). Therefore, leakiness cannot be directly translated into the relative rate of C4 overcycling, because the
concentration of CO2 via respiration in bundle-sheath
cells is not accounted for. When the concentrating action
of respiratory CO2 is correctly accounted for, ATP-use
efficiency of gross assimilation becomes relatively insensitive to short-term changes in PFD (Bellasio and Griffiths,
2014b) and the shape of the ATP-use efficiency response to
PFD (hyperbole, flat, or inverted hyperbole) becomes subject to the size of the mitochondrial respiratory CO2 flux in
bundle-sheath cells. These findings may also offer an explanation for the apparent discrepancy between leakinessderived estimates for ATP-use efficiency and quantum yield
(Farquhar, 1983). Namely, not all concentrated CO2 carries
an ATP investment cost. Leakage of CO2 that originates
from respiration does not decrease ATP-use efficiency, and
reports where this is not accounted for (e.g. Kromdijk et al.,
2008) are likely to overstate the effect of high leakiness on
ATP-use efficiency.
To conclude this paragraph, we summarize that leakiness
might increase at low PFD due to increased photorespiration
and an increased relative contribution of day respiration.
However, when plants are acclimated to low light, this pattern might be lost, primarily due to acclimation of day respiration. When estimates of leakiness increase at low PFD, this
may not be translated into a less efficient C4 cycle, as the ATP
cost might still be the same when the leaked CO2 stems from
respiratory sources. Finally, some species can display plasticity in ATP or NADPH production in either bundle-sheath
or mesophyll cells in order to achieve the energetic demands
with the available irradiance.
Improvements in understanding
biochemical diversity of C4 photosynthesis
In order to correctly interpret findings for leakiness, the
specific biochemical reactions that form the C4 pathway as
well as their spatial expression need to be fully known. C4
species have traditionally been categorized based on the
primary decarboxylating enzyme employed to liberate CO2
from C4 acids, which results in the following subgroups of
C4 species: NADP-malic enzyme (NADP-ME), NAD-malic
enzyme (NAD-ME) and PEP carboxykinase (PEPCK). Each
subgroup is associated with a variation of the biochemical
C4 cycle. Historically, most work has been dedicated to the
NADP-ME subgroup, which includes many agriculturally
relevant crop species.
Using the decarboxylation enzyme as a criterion to form
biochemical subgroups is often not satisfactory, as many species classified as NADP-ME or NAD-ME can express considerable activity of PEP-CK and can accumulate significant
amounts of aspartate. Furbank (2011) suggested that the relative co-expression of two decarboxylases (NADP-ME and
PEPCK) in maize could be subject to environmental conditions during growth (in particular light intensity) and might
also be linked to the relative abundance of PSII in bundlesheath chloroplasts. These suggestions have been followed up
by a number of recent studies, which together provide a more
comprehensive understanding of C4 biochemistry in Z. mays.
Pick et al. (2011) presented convincing evidence for the operation of two decarboxylation cycles in Z. mays, using PEPCK
and NADP-ME for C4 acid decarboxylation. One benefit
of such flexibility in C4 cycle biochemistry is the reduction
of gradients required to sustain transport fluxes of C4 acids
between mesophyll and bundle-sheath cells, assuming diffusion is the major driver for metabolic transport (Bräutigam,
2013). When aspartate and malate are both used as a transfer
C4 acid, the required malate gradient can be reduced while
achieving the same total C4 acid transfer (Fig. 2a). Significant
re-flux of alanine (instead of pyruvate) from the bundle sheath
to the mesophyll also helps to recover the amino groups split
from aspartate during transamination in the cytosol of bundle-sheath cells and to maintain the amino balance between
both compartments. Bellasio and Griffiths (2014a) noted that,
although operation of two C4 cycles in maize does not change
the total energetic requirement of the C4 pathway, it does
change the cell-type-specific energy balance. Flux through
PEPCK reduces the net transport of reductant from mesophyll to bundle-sheath chloroplasts via the malate shuttle and
PEP regeneration in bundle-sheath cells shifts ATP consumption from mesophyll chloroplasts to bundle-sheath cytosol.
Bellasio and Griffiths (2014a) modelled cell-type-specific
absorbed irradiance and metabolic reactions and concluded
that variable flux through PEPCK in maize allowed adequate
matching of energy supply and demand between mesophyll
and bundle-sheath cells, yielding greater plasticity in response
to light quantity and quality (Fig. 2b). Pick et al. (2011) and
Sommer et al. (2012) showed a developmental shift in leaves
of Z. mays and Cleome gynandra, where the fraction of C4
cycle flux through PEPCK relative to NAD-ME increased in
older leaves compared with middle-aged leaves.
So why is this relevant with regard to leakiness? Furbank
(2011) hypothesized that the fractional operation of PEPCK
in Z. mays could correlate with growth light intensity. Indeed,
Sharwood et al. (2014) recently showed a positive correlation
between abundance of PEPCK and light intensity during
growth. An increase in the fraction of C4 acid decarboxylation via PEPCK involves an increased demand for reductant
and ATP in the bundle-sheath compartment (Bellasio and
Griffiths, 2014a). Increased PSII content in bundle-sheath
chloroplasts could increase reduction of NADP+ via linear electron transport as suggested by Furbank (2011). The
Bundle-sheath leakiness in C4 photosynthesis | 3453
Fig. 2. Proposed benefits of biochemical plasticity in maize. (a) The diversity of C4 cycle biochemistry (forked C4 cycle) in maize allows the reduction
of gradients required to sustain transport fluxes of C4 acids between mesophyll and bundle-sheath cells, assuming diffusion is the major driver for
metabolic transport (Bräutigam, 2013). When aspartate and malate are both used as a transfer C4 acid, the required malate gradient can be reduced
while achieving the same total C4 acid transfer. (b) Although operation of two C4 cycles in maize does not change the total energetic requirement of
the C4 pathway significantly, it does change the cell-type-specific energy balance. Variable flux through PEPCK (Vpepck) therefore allows matching of
cell-specific demand to cell-specific absorbed irradiance (PFDa) and the corresponding supply of ATP (Jatp) and NADPH (Jnadph), which both vary
considerably as a function of the incident light spectral composition (blue, red, and green in this schematic). When PFDa in the bundle sheath is relatively
high (e.g. green irradiance), flux through Vpepck reduces net transport of reductant from the mesophyll to the bundle sheath and relaxes the requirement
for PEP regeneration in the mesophyll. As a result, variable flux through PEPCK yields greater plasticity in response to changes in light intensity and
spectral composition (Bellasio and Griffiths, 2014a). The relative size of PFDa, Jatp, Jnadph, Vpr, and Vpepck reflect the changes resulting from different
spectra of incident irradiance (blue, red, and green).
increased ATP demand can be matched via either chloroplastic or mitochondrial ATP production. This is relevant with
regard to acclimation of leakiness, because if the increased
bundle-sheath ATP requirement is met via mitochondrial
respiration in bundle-sheath cells (as is the case for obligate PEPCK species), this may explain why only high-lightgrown maize plants retain the increase in leakiness at low
PFD. Namely, any increase in mitochondrial CO2 release
within the bundle sheath will passively contribute to the
CO2-concentrating mechanism and this CO2 will not carry
an ATP penalty when leaking away without being fixed, as
explained in previous paragraphs. These hypothesized environmental influences on C4 physiology in maize require
more evidence. Here, the increasing use of systems-biology
approaches will be ideally suited to further investigate the
potential diversity of C4 biochemical pathways as well as
plasticity in the relative operation of parallel C4 cycles as a
function of environmental conditions.
3454 | Kromdijk et al.
Finally, when different decarboxylating routes operate
in parallel, it may be more difficult to interpret leakiness
values obtained with traditional methods. When leakiness is evaluated by means of Δ13C during gas exchange,
Rubisco fractionation is one of the most influencing factors, exhibiting by far the highest discrimination against
13
C in the C4 photosynthetic chain of events (27–30‰).
The implicit assumption in this analysis is that concentrated CO2 forms a single pool against which Rubisco can
discriminate. If we take the model species Z. mays as an
example, this assumption may not be justified, as PEPCK
is expressed specifically in the cytosol of bundle-sheath
cells, whereas NADP-ME is chloroplastic. Therefore, CO2
liberated from malate evolves in a different spatial location (bundle-sheath chloroplast) compared with CO2 from
aspartate (bundle-sheath cytosol). The validity of the ‘single pool’ assumption in Z. mays is therefore dependent on
the extent of mixing between both CO2 pools in bundlesheath cells.
Future research directions
While our knowledge and understanding of the finer details
of the C4 pathway are advancing rapidly, elegant regulatory
structures are emerging with positive- and negative-feedback
loops in place to passively fine-tune the balance between the
ancestral CBB cycle and the more recently evolved carbonconcentrating C4 cycle. With such diverse independent evolutionary origins (Sage et al., 2012), it seems only logical to
find considerable species-specific differences in biochemistry,
regulation of balance between both cycles, and bundle-sheath
leakiness, which we have shown in this review. Although
many aspects of this regulation are now becoming clear and
appear to allow greater phenotypic plasticity than previously
thought (Sage and McKown, 2006), answers inevitably lead
to more questions. For instance, if the parallel decarboxylation via NADP-ME and PEPCK conveys more flexibility in
responding to changes in PFD intensity or spectrum (Bellasio
and Griffiths, 2014a), as well as more balanced metabolism
between both cell types (Stitt and Zhu, 2014), does the variation in PEPCK activity within NADP-ME and NAD-ME
types represent an evolutionary selection pressure with respect
to the light environment? And if C4 light-use efficiency at low
PFD does not decline due to leakiness, and substantial acclimation potential of leakiness to low PFD exists, are there any
other intrinsic limitations for C4 systems not to have evolved
into canopy-forming trees (Sage, 2013)?
In isolated treatments, all aspects of the light environment
(intensity, constant or fluctuating, spectral composition) have
distinct effects on leaf photosynthetic efficiency. However,
only seldom is leakiness or C4 leaf or canopy photosynthetic
performance studied in plants that are growing under field
conditions, arguably the most relevant of settings with respect
to agricultural productivity. More data on a diverse range of
C4 species is required to understand which aspect of the light
environment is the most prominent influence for acclimation
under field conditions.
With respect to modelling of C4 photosynthesis and in particular bundle-sheath leakiness, whereas various model simplifications have been of great value in the past to analyse C4
photosynthetic behaviour, a number of these simplifications
have been shown to be insufficient to yield comprehensive
detail on the understanding of CBB/C4 balance and leakiness under the wide range of conditions applied (Ubierna
et al., 2011, 2013). It remains to be seen to what fine detail
the increasingly diverse picture of C4 biochemistry can be
reconciled with the simple and elegant models describing
C4 gas exchange (von Caemmerer, 2000) and carbon isotope
discrimination (Farquhar, 1983). However, if more complex
models are required, with these an even more prominent need
for parameterization will arise to put numbers on enzyme
activities, metabolite pools, and transport resistances under a
diverse range of conditions. The number of assumptions and
uncertainties in the methodology currently available to assess
bundle-sheath leakiness is already a major shortcoming. To
advance our understanding of CBB/C4 cycle balance and
leakiness, we need to be able to simultaneously probe various
components of the C4 pathway independent of the measurement of net gas exchange or carbon isotope discrimination by
the complete pathway. In particular, independent measures
for the CO2 concentration around Rubisco and the conductance of the leakage pathway are urgently needed to improve
analysis and interpretation of leakiness.
Acknowledgements
We would like to thank the organizers of the 2013 C4CAM plant biology
meeting, which provided food for thought with respect to many of the arguments that were put forward in this paper. We would also like to thank Dr
J. Kubásek and one anonymous reviewer for helpful comments to improve
the manuscript. ABC was supported by the Division of Chemical Sciences,
Geosciences and Biosciences, Office of Basic Energy Sciences, Photosynthetic
Systems through DE-FG02-09ER16062.
Appendix 1. Measurements of Δ13C
13
Δ can be measured over a period of time using the δ13C
values of plant biomass or instantaneously by combining
simultaneous measurements of leaf gas exchange and carbon
isotope ratios. In the first case, Δ13C is calculated as:
∆13C = ∆ obs − biomass =
δa − δ p
1+ δ p
Eq. A1
where δa and δp are the δ13C values of CO2 in air and plant
carbon, respectively, and Δobs-biomass represents an integrated
value over the period of tissue synthesis.
In the second case, discrimination is calculated using Evans
et al. (1986) equation:
∆ 13C = ∆ obs −online =
χ (δ o −δ
e
)
1 + δ o −χ (δ o −δ
e
)
Eq. A2
where δe and δo are the δ13C of the CO2 entering and leaving
the cuvette containing the photosynthesizing leaf and χ is:
Bundle-sheath leakiness in C4 photosynthesis | 3455
χ=
Ce
Ce −Co Eq. A3
Drouet JL, Bonhomme R. 1999. Do variations in local leaf irradiance
explain changes to leaf nitrogen within row maize canopies? Annals of
Botany 84, 61–69.
Ehleringer J, Pearcy RW. 1983. Variation in quantum yield for CO2
uptake among C3 and C4 plants. Plant Physiology 73, 555–559.
where Ce and Co are the 12CO2 molar fractions of the dry
air entering and leaving the cuvette. Δobs-online represents an
instantaneous measurement of discrimination corresponding
to the current leaf conditions.
Evans JR, Sharkey TD, Berry JA, Farquhar GD. 1986. Carbon isotope
discrimination measured concurrently with gas exchange to investigate
CO2 diffusion in leaves of higher plants. Australian Journal of Plant
Physiology 13, 281–292.
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