Shade compromises the photosynthetic efficiency of NADP-ME less than that of PEP-CK and NAD-ME C4 grasses.

The high energy cost and apparently low plasticity of C4 photosynthesis compared with C3 photosynthesis may limit the productivity and distribution of C4 plants in low light (LL) environments. C4 photosynthesis evolved numerous times, but it remains unclear how different biochemical subtypes perform under LL. We grew eight C4 grasses belonging to three biochemical subtypes [NADP-malic enzyme (NADP-ME), NAD-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK)] under shade (16% sunlight) or control (full sunlight) conditions and measured their photosynthetic characteristics at both low and high light. We show for the first time that LL (during measurement or growth) compromised the CO2-concentrating mechanism (CCM) to a greater extent in NAD-ME than in PEP-CK or NADP-ME C4 grasses by virtue of a greater increase in carbon isotope discrimination (∆P) and bundle sheath CO2 leakiness (ϕ), and a greater reduction in photosynthetic quantum yield (Φmax). These responses were partly explained by changes in the ratios of phosphoenolpyruvate carboxylase (PEPC)/initial Rubisco activity and dark respiration/photosynthesis (Rd/A). Shade induced a greater photosynthetic acclimation in NAD-ME than in NADP-ME and PEP-CK species due to a greater Rubisco deactivation. Shade also reduced plant dry mass to a greater extent in NAD-ME and PEP-CK relative to NADP-ME grasses. In conclusion, LL compromised the co-ordination of the C4 and C3 cycles and, hence, the efficiency of the CCM to a greater extent in NAD-ME than in PEP-CK species, while CCM efficiency was less impacted by LL in NADP-ME species. Consequently, NADP-ME species are more efficient at LL, which could explain their agronomic and ecological dominance relative to other C4 grasses.

Introduction

C4 photosynthesn class="Chemical">is pan> class="Chemical">is characterized by the operation of a CO2-concentrating mechanism (CCM) whereby atmospheric CO2 is initially fixed in the mesophyll cells (MCs) into C4 acids. These acids are subsequently decarboxylated in the bundle sheath cells (BSCs) releasing CO2 where Rubisco, the ultimate CO2-fixing enzyme, is located (Hatch, 1987). The CCM serves to raise the CO2 concentration in the BSCs, thus curbing photorespiration and CO2-saturating photosynthesis at current ambient CO2 concentrations ([CO2]) under high light (Hatch, 1987; Kanai and Edwards, 1999). The CCM requires additional energy costs compared with the C3 cycle associated with the regeneration of the C3 precursor phosphoenolpyruvate (PEP) and the overcycling of CO2. Nevertheless, under warm temperatures, C4 plants have a superior photosynthetic quantum yield (Фmax) relative to C3 plants (Ehleringer and Björkman, 1977; Pearcy ; Ehleringer and Pearcy, 1983; Zhu ). This explains the ecological dominance of C4 plants in open, high light (HL) environments and their disproportionately high global productivity relative to their small taxonomic representation (Ehleringer ; Brown, 1999; Edwards ).

Despite their success under HL, C4 plants experience low light (LL) under naturn class="Chemical">al conpan>ditionpan>s. C4 crops anpan>d grasses canpan> form denpan>se canpan>opies where a signpan>ificanpan>t proportionpan> of the leaf area pan> class="Chemical">is shaded, in addition to short-term LL exposures during the course of the day (Sage, 2014; Ort ). Numerous C4 grasses are adapted to the shade of the forest interior (Sage and Pearcy, 2000). Shading is expected to increase in the understorey of C4 grass-dominated ecosystems with predicted woody thickening under increasing atmospheric [CO2] (Bond and Midgley, 2012; Saintilan and Rogers, 2015). Consequently, it is important to investigate the efficiency of C4 photosynthesis under LL across diverse C4 plants.

C4 photosynthesn class="Chemical">is has evolved inpan>depenpan>denpan>tly manpan>y tipan> class="Gene">mes, resulting in three biochemical subtypes named after the primary C4 acid decarboxylase enzyme found in the BSCs, and they are NADP-malic enzyme (ME), NAD-ME, and phosphoenolpyruvate carboxykinase (PEP-CK) (Hatch 1987). PEP-CK operates as a secondary decarboxylase in many C4 species (Leegood and Walker, 2003; Furbank, 2011; Sharwood ; Wang ). However, the primary decarboxylase is generally associated with a suite of anatomical, biochemical, and physiological features (Gutierrez ; Hattersley, 1992; Kanai and Edwards, 1999; Ghannoum ), making it a suitable classification basis for the purpose of the current study investigating the efficiency of the C4-CCM. The grass family includes species from all biochemical subtypes (Sage and Pearcy, 2000; Edwards ), but our understanding of how different C4 subtypes respond and acclimate to LL environments remains limited.

It n class="Chemical">is well demonpan>strated that the C4 subtypes have differenpan>t leaf dry matter pan> class="Chemical">carbon isotope composition (δ13C) and Фmax. In particular, C4 grasses with the NAD-ME subtype (i.e. NAD-ME as the primary decarboxylase) show lower leaf δ13C (i.e. more negative values which are closer to the C3 range) and Фmax, while NADP-ME and PEP-CK species (i.e. those with NADP-ME and PEP-CK as the primary decarboxylases, respectively) show the highest and intermediate values, respectively (Hattersley, 1982; Ehleringer and Pearcy, 1983). There is a paucity of data comparing the response to shade of leaf δ13C and Фmax of the various C4 subtypes. Using 14 C4 grasses, Buchmann found that leaf δ13C values of NAD-ME species were most impacted by shade, followed by PEP-CK and NADP-ME species. In a large survey of C4 grasses, von Caemmerer reported that leaf δ13C was equally affected by growing season irradiance (winter versus summer) in NAD-ME and NADP-ME grasses. This discrepancy may be due to the fact that carbon isotope composition and discrimination are not significantly affected until photosynthetic photon flux density (PPFD) decreases below 700 μmol m–2 s–1 (Buchmann ).

In C4 plants, both photosynthetic and post-photosynthetic dn class="Chemical">iscriminpan>ationpan> factors determinpan>e leaf δ13C (Farquhar, 1983; vonpan> Caemmerer ). Reduced leaf δ13C under LL may be attributed to increased photosynthetic carbon isotope discrimination (ΔP) and BSC leakiness (ϕ) as a result of reduced CCM efficiency (Henderson ). For example, LL may reduce the activity of the C3 cycle to a greater extent than that of the C4 cycle, leading to greater overcycling. In turn, this will lead to higher ϕ and energetic cost of operating the C4-CCM. Consequently, we hypothesized that LL will differentially compromise the C4-CCM efficiency depending on the biochemical subtype. In particular, we predicted that LL will increase leaf δ13C and ΔP, and reduce Фmax to a greater extent in NAD-ME grasses, followed by PEP-CK and NADP-ME species (Hypothesis 1).

Short- and long-term photosynthetic responses to LL are expected to differ. Following long-term exposure to LL (shade), the photosynthetic apparatus commonly acclimates to maximize light use efficiency (Björkman, 1981; Boarn class="Disease">dmanpan>, 1977; Sage anpan>d McKownpan>, 2006). Depenpan>dinpan>g onpan> the planpan>t species anpan>d ecotype, acclimationpan> may be minpan>impan> class="Chemical">al or profound (Ward and Woolhouse, 1986, ; Björkman and Holmgren, 1966). Overall, acclimation of C3 and C4 plants to shade involves partitioning of photosynthetic nitrogen (N) away from Rubisco towards the light-harvesting processes (Boardman, 1977; Björkman, 1981; Hikosaka and Terashima, 1995; Evans and Poorter, 2001; Walters, 2005; Tazoe ; Pengelly ). NAD-ME species are known to have higher leaf N content and a greater N fraction invested in Rubisco relative to NADP-ME species (Ghannoum ). Hence, the former subtype may have a greater flexibility to reallocate N under shade especially since, as mentioned above, LL is expected to reduce the activity of the C3 cycle (e.g. Rubisco) more than the C4 cycle [e.g. phosphoenolpyruvate carboxylase (PEPC)]. However, optimal photosynthetic acclimation of C4 photosynthesis to shade is expected to involve parallel reductions in the activities of the C3 and C4 cycles in order to curb leakiness and maintain an efficient CCM and quantum yield (Bellasio and Griffiths, 2014, b), which does not seem to be the case for NAD-ME species in Buchmann . Consequently, we hypothesized that NAD-ME species will exhibit a greater photosynthetic acclimation in response to shade relative to the other two subtypes. This will manifest as a greater photosynthetic down-regulation and higher leakiness in the LL-acclimated leaves of NAD-ME species relative to the other two subtypes (Hypothesis 2).

To address these two hypotheses, we investigated the photosynthetic responses of eight C4 grasses belonging to three biochemicn class="Chemical">al subtypes (Table 1) to short-term (200 µmol quanpan>ta m–2 s–1 versus 2000 µmol quanpan>ta m–2 s–1) anpan>d lonpan>g-term (16% versus 100% sunpan>light; Supplepan> class="Gene">mentray Fig. S1A at JXB online) light treatments. We sought to elucidate the underlying mechanisms by describing changes in photosynthetic rates and enzyme activities, and in the CCM efficiency as described by leakiness and quantum yield. Our results indicated that NADP-ME species are generally more efficient at LL due to effective co-ordination of the C4 and C3 cycles.

Table 1.

List of C4 grasses used in the current study

C4 subtype	C4 tribe	Species
NADP-ME	Paniceae	Cenchrus ciliaris Panicum antidotale
	Andropogoneae	Sorghum bicolor Zea mays
PEP-CK	PaniceaeChloridoideae	Megathyrsus maximus Chloris gayana
NAD-ME	PaniceaeChloridoideae	Panicum coloratum Leptochloa fusca

Ln class="Chemical">ist of C4 grasses used inpan> the currenpan>t study

Materials and methods

Plant culture

The experin class="Gene">ment was conpan>ducted inpan> a naturpan> class="Chemical">ally lit glasshouse chamber (5 m3) during the Australian summer. Within the chamber, an aluminium structure (1.5 × 5 m3) was covered with white shade cloth (Premium Hortshade Light, Model No. 428976, Coolaroo, VIC, Australia). A PPFD of ~100 μmol quanta m–2 s–1 was achieved inside the shade structure by adjusting the number of cloth layers. The impact of heavy shade during cloudy days was minimized by supplementing external growth light (LimiGrow Pro S325, Emeryville, CA, USA) to achieve a leaf-level PPFD of 100 μmol m–2 s–1. The chamber temperature was maintained at 28/22 °C for day/night with an in-built glasshouse temperature-controlled system. The air temperature and relative humidity (RH) at leaf level were monitored using Rotronic HC2-S3 (Bassersdorf, Switzerland) sensors placed in a shield vented with a 12 V fan. A Licor quantum sensor (LI-190, Lincoln, NE, USA) was mounted at the leaf level to monitor incident PPFD in the unshaded and shaded glasshouse structure. Data from these sensors were stored using a Licor data logger (LI-1400). Through the experiment, average midday ambient PPFD, T, and RH at leaf level were 741 μmol m–2 s–1, 25 ºC, and 69% in the sun treatment. These figures in the shade treatment were 119 μmol m–2 s–1, 26 °C, and 65% (see Supplementary Fig. S1C). Hence, the shade treatment was equivalent to 16% of sunlight measured in the sun treatment, averaged over the experimental period (Supplementary Fig. S1). Instantaneous leaf temperature was measured using a hand-held, non-contact infrared thermometer (AGRI-THERM II™, Chino Hills, CA USA). On average, shaded leaves were 1–2 °C cooler than sun leaves (Supplementary Fig. S1D).

Locn class="Chemical">ally collected soil was sunpan> dried (Pinpan>to ), coarsely sieved, anpan>d added to 3.5 litre cylinpan>dricpan> class="Chemical">al pots. Pots were watered to 100% capacity and transferred to the glasshouse chamber. Seeds for grasses used in this study (Table 1) were obtained from the Australian Plant Genetic Resources Information System (QLD, Australia) and Queensland Agricultural Seeds Pty. Ltd. (Toowoomba, Australia). In the current study, we used 2–3 representative species belonging to each of the C4 subtypes. Within each subtype, species were selected from different C4 origins (tribes in Table 1) to randomize the C4 origin effect, and hence focus on the subtype effect.

Seeds were germinated in a comn class="Gene">mercipan> class="Chemical">al Osmocote® professional, seed raising and cutting mix (Scotts, Bella Vista, NSW, Australia). Three to four weeks after germination, two healthy seedlings were transplanted into each of the soil-filled and pre-irrigated pots. A week later, one healthy seedling was left in each pot while the other was removed. Plants were allowed to grow until the 5–6 leaf stage in full sunlight before they were transferred to the shade treatment. There were eight pots per species and light treatment. Pots were randomly positioned and regularly rotated within each treatment throughout the experiment. Plants were well watered daily with added commercial soluble fertilizer (Aquasol, N:P:K=23.3:3.95:14; Yates, Wetherill Park, NSW, Australia).

Leaf gas exchange measurements

Leaf gas exchange was n class="Gene">measured with a portable openpan> gas exchange system (LI-6400XT, LI-COR). The younpan>gest last fully expanded leaf (LFEL) onpan> the mainpan> stem of a 6- n class="Species">to 9-week-old plant was measured at a leaf temperature of 28 °C between 10.00 h and 14.00 h. Shaded plants developed a minimum of three new leaves under shade before gas exchange measurements were made.

Each leaf was allowed to reach a steady state, at least 20 minpan>, pan> class="Chemical">CO2 assimilation rate (A) at ambient [CO2] of 407 µbar, PPFD of 2000 μmol m–2 s–1, and RH of 50–70%. After this, a steady-state measurement [performed concurrently with tunable diode-laser (TDL) analysis; see below for details] was taken. Subsequently, the response of A to step increases of intercellular CO2 (Ci), the A–Ci curve, was measured by raising the LI-6400XT leaf chamber [CO2] in 10 steps between 50 µbar and 1500 µbar. After completing the A–Ci curve at PPFD 2000 μmol m–2 s–1, the leaf was allowed to reach a steady state of gas exchange at saturating CO2 (660 µbar) before measuring the responses to PPFD. The light response curve was measured from HL to LL (11 steps) followed by measurements of dark respiration (Rd) at ambient [CO2] of 407 µbar after 20 min in a dark leaf chamber. Prior to LL steady-state measurement (performed concurrently with TDL analysis; see below for details), the same leaf was allowed to reach a steady-state A similarly to HL measurements, except PPFD was controlled at 250 μmol m–2 s–1. This was followed by measuring the A–Ci curve at the same light (LL) as described above. There were 3–4 replicates per treatment. The initial slope (IS) of the A–Ci curve was estimated for the linear part of the A–Ci curve measured at HL where Ci is <55 µbar. The aximum CO2 assimilation rate (A) on the A–Ci curve was considered as the CO2-saturated rate (CSR). The A–Ci curves measured at LL could not be used for accurate IS determination due to low overall rates. The light response curves were fitted using the following equation (Ögren and Evans, 1993):

where, I=absorbed irradiance, we assun class="Gene">med absorptance=0.85; A=n class="Chemical">CO2 assimilation rate at given light; Φnls=maximum quantum yield of PSII; Amax=light-saturated CO2 assimilation rate; and θ=curvature factor of the light response curve. In addition, the slope of a linear part of the light response curve (PPFD <120 μmol m–2 s–1) was estimated as the ‘apparent’ maximum quantum yield of PSII (Фmax). We consider this estimate in our further analysis.

Photosynthetic carbon isotope discrimination

n class="Disease">Bundle sheath leakiness (ϕ) was determinpan>ed by n class="Gene">measuring real-time 13CO2/12CO2 isotope discrimination using a LI-6400XT interfaced with a tunable diode laser, TDL (TGA100, Campbell Scientific, Inc., Logan, UT, USA). The mean SD for repeated TDL measurements of δ13C values for a reference gas was 0.09‰. Observed photosynthetic carbon isotope discrimination against (ΔP) was calculated using (Evans ):

where δe, δo, Ce, and Co are the δ13C (δ) and n class="Chemical">CO2 mole fractionpan> (C) of the air enpan>terinpan>g (e) and leavinpan>g (o) the leaf chamber n class="Gene">measured with the TDL-LI-6400 set up. Leakiness at high light (ϕh) was calculated using the model of Farquhar (1983) as modified by Pengelly , 2012) and von Caemmerer :

where t, the ternary correction factor, n class="Chemical">is calculated as per Farquhar and Cernusak (2012):

where E n class="Chemical">is the transpirationpan> rate, n class="Chemical">gtac the total conductance to CO2 diffusion including boundary layer and stomatal conductance (von Caemmerer and Farquhar, 1981). The combined fractionation factor through the leaf boundary layer and stomata is denoted by a′,

Definition and units for the variables included in the above equation are described in Table 2, but briefly, Ca, Ci, and Cls are the ambient, intercellular and leaf surface n class="Chemical">CO2 mole fractionpan>s respectively; ab (2.9‰) pan> class="Chemical">is the fractionation occurring through diffusion in the boundary layer; s (1.8‰) is the fractionation during leakage of CO2 out of the bundle sheath assuming there is no HCO3– leakage out of BSCs (Henderson ); a (4.4‰) is the fractionation due to diffusion in air (Evans ); and ai is the fractionation factor associated with the dissolution of CO2 and diffusion through water (1.8‰).

Table 2.

Statistical summary

Parameter	Species	Treat	Species×treatment	Species (rand)	Subtype	Treatment	Subtype×treatment
Total DM (g per plant)	***	***	***	***	*	**	**
Total leaf area (m2 per plant)	***	***	***	***	ns	*	*
Root/shoot DM	***	***	***	***	ns	**	ns
LMA (g m–2)	***	***	***	***	ns	*	ns
Leaf Nmass (mg g–1)	***	*	***	***	ns	ns	ns
Leaf Narea (gm–2)	***	***	***	**	ns	***	ns
Leaf NUE	***	***	**	***	0.10	**	*
∆DM (‰)	***	***	***	***	*	*	*
PNUE (µmol CO2 s–1 g–1 N)	***	***	***	NA	0.10	0.07	0.06
PWUE (µmol CO2 mol–1 H2O)	***	*	*	***	ns	ns	ns
A h at HL (µmol m–2 s–1)	***	***	***	***	0.09	**	*
A l at LL (µmol m–2 s–1)	***	**	***	**	ns	*	*
g sh at HL (µmol m–2 s–1)	***	***	**	***	ns	**	0.07
g sl at LL (µmol m–2 s–1)	*	ns	ns	*	ns	ns	ns
∆Ph at HL (‰)	***	***	*	***	ns	0.10	ns
∆Pl at LL (‰)	***	ns	ns	***	ns	ns	ns
C i/Cah at HL	***	***	0.06	***	ns	ns	ns
C i/Cal at LL	***	ns	*	0.07	ns	ns	ns
Leakiness (Фh) at HL	***	**	*	***	ns	**	ns
Leakiness (Фl) at LL	***	ns	ns	***	ns	ns	ns
R d (µmol m–2 s–1)	***	***	*	**	ns	0.06	ns
IS at HL (µmol m–2 s–1 bar–1)	***	***	***	***	ns	*	0.10
CSR at HL (µmol m–2 s–1)	***	***	***	***	0.07	**	*
IS/CSR at HL	***	ns	*	*	ns	ns	ns
A max (µmol m–2 s–1)	***	***	***	NA	0.10	**	*
Фmax (mol CO2 mol-1quanta)	***	***	***	***	0.08	*	*
Curvature factor (θ)	***	0.08	***	*	0.10	0.08	*
Initial Rubisco activity	*	***	*	*	ns	*	*
Rubisco activity (µmol m–2 s–1)	ns	***	ns	*	ns	*	ns
Rubisco sites (µmol m–2)	***	***	***	***	ns	*	ns
Rubisco activation (%)	***	***	***	*	ns	0.10	0.07
PEPC activity (µmol m–2 s–1)	***	***	***	***	0.10	**	*
PEPC/Rubisco activity	***	***	***	***	0.08	*	*
NADP-ME activity (µmol m–2 s–1)	***	***	***	NA	*	*	*
NAD-ME activity (µmol m–2 s–1)	***	***	***	***	0.10	*	ns
PEP-CK activity (µmol m–2 s–1)	***	***	***	***	ns	*	ns
DCs (µmol m–2 s–1)	***	***	***	***	ns	*	0.10
Protein (g m–2)	*	***	***	NA	ns	*	ns

Summary of statistical analysis using two-way ANOVA to test for the effects of species and light treatment, and a linear-mixed effect model to test subtype and light treatment effects where species were considered as a random variable.

ns, not significant (P>0.05); *P<0.05; ** P<0.01; ***P<0.001

Statn class="Chemical">isticpan> class="Chemical">al summary

Summary of statn class="Chemical">isticn class="Chemical">al analysis using two-way ANOVA to test for the effects of species and light treatment, and a linear-mixed effect model to test subtype and light treatment effects where species were considered as a random variable.

and are defined as in von Caemn class="Gene">merer :

and

where b3 n class="Chemical">is the fractionpan>ationpan> by Rubisco (30‰); b4 is the combined fractionation of the conversion of CO2 to HCO3– and PEP carboxylation (–5.41‰ at 28 °C)(Henderson ; Mook ); f is the fraction associated with photorespiration; and Vo and Vc are the rates of oxygenation and carboxylation, respectively. Under HL we assumed no photorespiration, hence the term (Pengelly , 2012; Ubierna ; von Caemmerer ). The reference gas supplied to the LI-6400XT during gas exchange measurements had δ13C= –5.5‰. Therefore, the value for the fractionation factor e associated with respiration was calculated assuming recent photoassimilates as the respiratory substrate (Stutz ). Thus, e equalled the difference between δ13C in the CO2 sample line in LI-6400XT and that in the glasshouse chamber (–8‰; Tazoe ). A and Rd (von Caemmerer ) denote the CO2 assimilation rate and day respiration, respectively; Rd was assumed to equal measured dark respiration. We assumed mesophyll conductance, gm=1.4 mol m–2 s–1 at 28 °C (for C4 the model plant Setaria viridis) (Ubierna ).

n class="Disease">Leakiness at low light (ϕl) was calculated as described by Bellasio and Griffiths (2014) and Ubierna . Briefly, electron transport flux (Jt) at low light was derived by deploying the light-limited C4 photosynthesis model to calculate Cs (CO2 mole fraction in the bundle sheath), Vp (PEP carboxylation rate), Vc (Rubisco carboxylation rate), and Vo (Rubisco oxygenation rate) at LL using the C4 model (von Caemmerer, 2000) (see Supplementary Appendix S1). It should be noted that we used measured values for the fraction of PSII in BSCs, α (0 for NADP-ME and 0.2 for PEP-CK and NAD-ME) and half of the reciprocal of Rubisco specificity, γ* (0.000255, 0.00023, and 0.000233 for NADP-ME, NAD-ME, and PEP-CK, respectively) (Table 2; Sharwood ) for biochemical subtypes of C4 photosynthesis during the calculation of Jt. These parameters were then used to calculate (the combined effects of fractionations by the CO2 dissolution, hydration, and PEPC activity at LL) and (Rubisco fractionation at LL by accounting for the fraction during respiration and photorespiration) (Farquhar, 1983; Ubierna ) to calculate ϕl in the following equation,

other variables and unit are as defined in Table 2, but briefly Cm n class="Chemical">is the n class="Gene">mesophyll CO2 mole fraction given by

Subtype-specific vn class="Chemical">alues for α and γ* improved the estimationpan>s of ϕl as demonpan>strated inpan> Supplen class="Gene">mentary Fig. S7.

Activity of Rubisco, PEPC, NADP-ME, NAD-ME, and PCK

Following gas exchange n class="Gene">measurepan> class="Gene">ments, replicate discs (0.4–1 cm2) were rapidly frozen in liquid N then stored at –80 °C until analysed. Two sets of extractions were performed to complete the biochemical analysis. For Rubisco activity, activation, and content, PEPC and NADP-ME activity, and soluble protein assays, the extraction buffer was purged of CO2 overnight by bubbling a weak jet of nitrogen gas through the basic buffer [50 mM EPPS-NaOH (pH 7.8), 5 mM MgCl2, 1 mM EDTA]. Each leaf disc was extracted in 0.8 ml of ice-cold extraction buffer [50 mM EPPS-NaOH (pH 7.8), 5 mM DTT, 5 mM MgCl2, 1 mM EDTA, 10 μl of protease inhibitor cocktail (Sigma), 1% (w/v) polyvinyl polypyrrolidone (PVPP)] using a 2 ml Tenbroeck glass homogenizer kept on ice. Chlorophyll content was estimated according to Porra by mixing 100 µl of total extract with 900 µl of acetone. The extract was then centrifuged at 15 000 g for 1 min and the supernatant was used for the subsequent assays. For Rubisco content, subsamples of the supernatant were incubated for 10 min in activation buffer [50 mM EPPS (pH 8.0), 10 mM MgCl2, 2 mM EDTA, 20 mM NaHCO3]. Rubisco content was estimated by the irreversible binding of [14C]CABP (2-C-carboxyarabinitol 1,5-bisphosphate) to the fully carbamylated enzyme (Sharwood ). Extractable soluble proteins were measured using the Pierce Coomassie Plus (Bradford) protein assay kit (Thermo Scientific, Rockford, IL, USA).

The activities of the photosynthetic enzyn class="Gene">mes Rubisco, PEPC, and NADP-ME were measured using spectrophotometric assays as described previously (Jenkins ; Ashton ; Sharwood , 2014, 2016; Pengelly ). Briefly, initial Rubisco activity was measured in assay buffer containing 50 mM EPPS-NaOH (pH 8), 10 mM MgCl2, 0.5 mM EDTA, 1 mM ATP, 5 mM phosphocreatine, 20 mM NaHCO3, 0.2 mM NADH, 50 U of creatine phosphokinase, 0.2 mg of carbonic anhydrase, 50 U of 3-phosphoglycerate kinase, 40 U of glyceraldehyde-3-phosphate dehydrogenase, 113 U of triose-phosphate isomerase, and 39 U of glycerol-3-phosphate dehydrogenase, and the reaction initiated by the addition of 0.22 mM ribulose-1,5-bisphosphate (RuBP). For maximal Rubisco activity, the supernatant was activated in assay buffer for 10 min at 25 °C before initiation of the reaction. Rubisco activation was calculated as the initial/maximal Rubisco activity ratio. Our Rubisco activity from in vitro assays was slightly lower than CO2 assimilation rates. Hence, in the current study, we presented Rubisco activity estimated from Rubisco sites measured with CABP assay and published Rubisco Kcat for individual species (Sharwood ), and Rubisco activation values are from in vitro initial and activated Rubisco assays.

n class="Gene">PEPC activity was n class="Gene">measured in assay buffer [50 mM EPPS-NaOH (pH 8.0), 0.5 mM EDTA, 10 mM MgCl2, 0.2 mM NADH, 5 mM glucose-6-phosphate, 0.2 mM NADH, 1 mM NaHCO3, 1 U of malate dehydrogenase (MDH)] after the addition of 4 mM PEP. NADP-ME activity was measured in assay buffer [50 mM NADP-ME buffer (pH 8.3), 4 mM MgCl2, 0.5 mM NADP, 0.1 mM EDTA] after the addition of 5 mM malic acid.

The activity of n class="Gene">PEP-CK was n class="Gene">measured in the carboxylation direction using the method outlined previously (Koteyeva ; Sharwood ). For PEP-CK and NAD-ME activity, a separate leaf disc was homogenized in extraction buffer containing 50 mM HEPES (pH 7.5), 2 mM EDTA, 0.05% Triton, 5 mM DTT, 1% PVPP, and 2 mM MnCl2 using a 2 ml Tenbroeck glass homogenizer kept on ice. The extract was centrifuged at 21 130 g for 1 min and the supernatant used for PEP-CK and NAD-ME activity assays. PEP-CK activity was measured in assay buffer containing 50 mM HEPS (pH 6.3), 4% β-mercaptoethanol, 100 mM KCl, 90 mM KHCO3, 0.5 mM ADP, 2 mM MnCl2, 0.2 mM NADH, 6 U of MDH, and 5 mM aspartic acid after the addition of 10 mM PEP. NAD-ME activity was measured in 25 mM Tricine (pH 8.3), 5 mM DTT, 2 mM NAD, 0.1 mM acetyl-CoA, 4 mM MnCl2, and 2 mM EDTA after the addition of 5 mM malic acid. Enzyme activity was calculated by monitoring the decrease/increase of NADH+ absorbance at 340 nm with a UV-VIS spectrophotometer (model 8453, Agilent Technologies Australia, Mulgrave, Victoria).

SDS–PAGE and immunoblot analysis of photosynthetic proteins

n class="Chemical">SDS–PAGE and immunpan>oblot ann class="Chemical">alysis of photosynthetic proteins were performed as described in Sharwood . The procedures are described below.

Subsamples of totn class="Chemical">al leaf extracts used for enpan>zypan> class="Gene">me assays were mixed with 0.25 vols of 4× LDS buffer (Invitrogen) containing 100 mM DTT and placed in liquid nitrogen, then stored at –20 °C until they were analysed. For confirmatory visualization, protein samples were separated by SDS–PAGE in TGX Any kD (BioRad) pre-cast polyacrylamide gels buffered with 1× Tris-glycine SDS buffer (BioRad) at 200 V using the Mini-Protean apparatus at 4 °C. Proteins were visualized by staining with Bio-Safe Coomassie G-250 (BioRad) and imaged using the VersaDoc imaging system (BioRad).

For immunoblot ann class="Chemical">alyses, samples of totn class="Chemical">al leaf proteins were separated by SDS–PAGE as outlined above, then transferred at 4 °C to nitrocellulose membranes (0.45 µm; BioRad) using the Xcell Surelock western transfer module (Invitrogen) buffered with 1× Transfer buffer [20 × 25 mM Bicine, 25 mM Bis-Tris, 1 mM EDTA, 20% (v/v) methanol]. After 1 h transfer at 30 V, the membrane was placed in blocking solution [3% (w/v) skim milk powder in Tris-buffered saline (TBS); 50 mM Tris–HCl pH 8, 150 mM NaCl] for 1 h at room temperature with gentle agitation.

Primary antisera raised in rabbit against tobacco Rubisco (prepared by S.M. Whitney) was diluted 1:4000 in TBS before incubation for 1 h with membranes at room temperature with gentle agitation. Antiserum raised against PEPC (Cat. AS09 458) was obtained from AgriSera and diluted 1:2000 with TBS. For NADP-ME and PEP-CK, synthetic peptides based on monocot amino acid sequences for each protein were synthesized by GL Biochem and antisera were raised against each peptide in rabbits. The reactive antiserum was the antigen purified for use in immunoblot analysis (GL Biochem). The NADP-ME and PEP-CK antisera were diluted in TBS 1:1000 and 1:500, respectively. All primary antisera were incubated with membranes at room temperature for 1 h with gentle agitation before washing three times with TBS. Secondary goat anti-rabbit antiserum conjugated to horseradish peroxidase (HRP; Cat. NEF 812001EA, Perkin Elmer) was diluted 1:3000 in TBS and incubated with the membranes for 1 h at room temperature followed by three washes with TBS. Immunoreactive peptides were detected using the Immun-Star Western C kit (Cat. 170-5070, BioRad) and imaged using the VersaDoc.

Leaf nitrogen and carbon isotope analyses

Following gas exchange and leaf dn class="Chemical">isc samplinpan>g, the remainpan>der of the LFEL was cut anpan>d its area was n class="Gene">measured using a leaf area meter (LI-3100A, LI-COR). The LFEL was oven-dried, weighed, then milled to a fine powder. Leaf N content was determined on the ground leaf tissue samples using a CHN analyser (LECO TruSpec, LECO Corp., MI, USA). Leaf mass per area (LMA, g m–2) was calculated as total leaf dry mass/total leaf area. Leaf N per unit area (Narea) was calculated as (mmol N g–1)×LMA (g m–2). For leaf δ13C, ground leaf samples were combusted in a Carlo Erba Elemental Analyser (Model 1108) and the released CO2 was analysed by MS. The δ13C=[(Rsample–Rstandard)/Rstandard]×1000, where Rsample and Rstandard are the 13C/12C ratio of the sample and standard (Pee Dee Belemnite), respectively. Photosynthetic carbon isotope discrimination based on leaf dry matter δ13C (∆DM) was calculated as described by Farquhar and Richards (1984):

where δa and δp are the δ13C vn class="Chemical">alues inpan> the n class="Chemical">glasshouse air (assumed to be –8‰) and in the leaf bulk material, respectively.

PWUE and PNUE calculations

Photosynthetic n class="Chemical">water use efficienpan>cy (PWUE) was calculated as A (µmol m–2 s–1)/gs (mol m–2 s–1). Photosynthetic nitrogen use efficiency (PNUE) was calculated as A (µmol m–2 s–1)/leaf Narea (mmol m–2).

Plant harvest

Plants were harvested 10–11 weeks after transplanting. At harvest, leaves were separated from stems. Totn class="Chemical">al leaf area was determinpan>ed usinpan>g a Licor LI-3100A leaf area n class="Gene">meter. Roots were washed free of soil. Plant materials were oven-dried at 80 ºC for 48 h before dry mass (DM) was measured. Total plant DM included leaf, stem, and root DM. Leaf nitrogen use efficiency (NUE) was calculated as the ratio of total plant DM (g per plant)/total leaf N content (mg).

Statistical analysis

Growth, gas exchange, enzyn class="Gene">me assay, anpan>d leaf pan> class="Chemical">nitrogen analyses were performed on 3–4 replicates per treatment combination (species×light). For species as a main effect, the relationship between various response variables and the main effect (species and light treatment) and their interactions were fitted using the linear model in R (R Foundation for Statistical Computing, Vienna, Austria) (R Core Team, 2015). Since the numbers of species within each subtype were unequal and measurements were taken on multiple individuals within a species, each unit cannot be considered as a true independent replicate. Therefore, a linear mixed effect model (lmer) was used to estimate the fixed effect associated with light treatment and subtype, where species were treated as a random variable. For each response variable, the models containing all possible fixed effects were fitted using the lme4 package (Bates ) in R. The model residues were tested for normality, and data transformation was carried out to achieve a normal distribution, if required. Significance tests were performed with a parametric bootstrap by using the ‘pbkrtest’ package in R (Halekoh and Højsgaard, 2014). Briefly, a linear mixed effect model (fitted with maximum likelihood), full and restricted models, was used as a sample to generate the likelihood ratio statistic (LRT) after 1000 bootstraps. To estimate the P-value, LRT divided by the number of degrees of freedom was assumed to be F-distributed where denominator degrees of freedom are determined by matching the first moment of reference distribution.

Results

Throughout thn class="Chemical">is study, the species effect was highly signpan>ificant for all parameters and generally is not described below (Table 2).

Plant growth and leaf chemistry

Across treatn class="Gene">ments, n class="Gene">PEP-CK species had a higher average plant DM and total leaf area relative to NADP-ME and NAD-ME species (P<0.05; Table 2; Fig. 1A; Supplementary Table S1). Shade reduced plant DM to a greater extent in NAD-ME (–95%) and PEP-CK (–92%) relative to NADP-ME (–81%) species (Table 2; Fig. 1A; Supplementary Table S1). Total plant DM and total leaf area were linearly correlated across the species and light treatments (R2=0.9 for the log relationship) (Fig. 1C). The effect of shading on plant DM and leaf area increased linearly with shaded plant DM (R2=0.97 and 0.89, respectively). The root to shoot ratio did not vary according to subtype but was substantially reduced by shade in all species (Table 2; Supplementary Table S1). There was no significant subtype effect on LMA, leaf Nmass, or leaf Narea, while shade reduced LMA and leaf Narea (but not leaf Nmass) in most species (Table 2; Supplementary Table S1).

Fig. 1.

Total plant dry mass and leaf area. (A) Total plant dry mass (DM), (B) CO2 assimilation rate measured at ambient [CO2], (C) relationship between the log of total leaf area and the log of total DM, and (D) dark respiration (Rd) for eight C4 grasses belonging to three biochemical subtypes and grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. For (A) and (D), statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001. In (B), measurements were made at 2000 (HL) and 250 (LL) μmol quanta m–2 s–1 for both control and shade treatments. Letters indicate the ranking (from lowest=a) within each subtype using multiple-comparison Tukey’s post-hoc test.

Totn class="Chemical">al planpan>t dry mass anpan>d leaf area. (A) Totpan> class="Chemical">al plant dry mass (DM), (B) CO2 assimilation rate measured at ambient [CO2], (C) relationship between the log of total leaf area and the log of total DM, and (D) dark respiration (Rd) for eight C4 grasses belonging to three biochemical subtypes and grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. For (A) and (D), statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001. In (B), measurements were made at 2000 (HL) and 250 (LL) μmol quanta m–2 s–1 for both control and shade treatments. Letters indicate the ranking (from lowest=a) within each subtype using multiple-comparison Tukey’s post-hoc test.

Leaf gas exchange at low and high light

Overall, there was no signpan>ificanpan>t subtype effect onpan> pan> class="Chemical">CO2 assimilation rates and stomatal conductance measured at HL (Ah and gsh, respectively) and LL (Al and gsl, respectively) (P>0.05, Table 2). However, there was a significant treatment and subtype×treatment effect on both Ah and Al (P<0.05; Table 2). In particular, shade reduced Ah and Al to a greater extent in NAD-ME (–62% and –27%, respectively) relative to PEP-CK (–46% and –15%, respectively) and NADP-ME –40% and 0%, respectively) species (Fig. 1B; Supplementary Table S2). Furthermore, under shade, NADP-ME species had the highest and NAD-ME species had the lowest Ah and gh, indicating that photosynthesis and stomatal conductance acclimated to shade more strongly in the latter species (Fig. 1B; Supplementary Table S2). The CO2 assimilation rate was strongly correlated with stomatal conductance across all species and treatments (R2=0.86) (Fig. 2A). Consequently, Ci/Ca was constant and, together with PWUE, did not vary according to the subtype or light treatment (Table 2; Supplementary Table S2).

Fig. 2.

Relationships among physiological and in vivo derived parameters. CO2 assimilation (Ah), stomatal conductance (gh), IS, and CSR derived from A–Ci curves measured at high light, Amax and Φmax derived from light response curves measured at saturating [CO2], and leaf Narea for eight C4 grasses belonging to three biochemical subtypes grown in control (full sunlight; blue) or shade (16% of natural sunlight) (red) environments. Straight lines are linear regressions for all data points.

Relationships among physiologicn class="Chemical">al anpan>d inpan> vivo derived paran class="Gene">meters. CO2 assimilation (Ah), stomatal conductance (gh), IS, and CSR derived from A–Ci curves measured at high light, Amax and Φmax derived from light response curves measured at saturating [CO2], and leaf Narea for eight C4 grasses belonging to three biochemical subtypes grown in control (full sunlight; blue) or shade (16% of natural sunlight) (red) environments. Straight lines are linear regressions for all data points.

R d did not differ between the subtypes but it was reduced by shade in n class="Gene">NADP-ME and n class="Gene">NAD-ME species (Fig. 1D; Table 2; Supplementary Table S2). For control plants, the Rd/A ratio (measured at growth light) was lowest in PEP-CK species; shade increased Rd/A less in NADP-ME (+158%) relative to PEP-CK (+374%) and NAD-ME (+341%) species (Table 2; Supplementary Table S2). CO2 assimilation rate measured at HL, Ah, and Rd showed good linear relationships to leaf Narea across species (R2=0.59 and R2=0.54, respectively). PNUE was marginally lower (P=0.1) in NAD-ME relative to NADP-ME and PEP-CK species, and was reduced by shade mostly in NAD-ME (–28%) and PEP-CK (–19%) (Table 2; Supplementary Table S2). Leaf NUE was reduced to a greater extent in NADP-ME and NAD-ME species (–41% and –39%, respectively) relative to PEP-CK species (Table 2; Supplementary Table S1).

Photosynthetic CO2 response curves

The initin class="Chemical">al slopes (pan> class="Chemical">ISs) of the A–Ci curvesand CO2-saturated rates (CSRs) were estimated from measurements at HL (Supplementary Fig. S2). In control plants, the IS and CSR did not vary with subtypes, but were reduced by shade to a greater extent in NAD-ME (–77% for IS and –64% for CSR) than PEP-CK (–49% for IS and CSR) and NADP-ME species (–46% for IS and –39% for CSR) (Tables 2, 3). Consequently, CSR of shaded plants was lowest in NAD-ME, intermediate in PEP-CK, and highest in NADP-ME species (Tables 2, 3). There was a strong linear relationship between IS and CSR irrespective of treatment and subtype (R2=0.73) (Fig. 2B).

Photosynthetic light response curves

The light-saturated photosynthesn class="Chemical">is rate, Amax, anpan>d photosynpan>thetic quanpan>tum yield, Фmax, were estimated from the light responpan>se curves of photosynpan>thespan> class="Chemical">is measured at saturating CO2 (Supplementary Fig. S3). In control plants, Amax and Фmax did not vary with subtypes (Tables 2, 3; Fig. 3G). Shade reduced Amax and Фmax to a greater extent in NAD-ME species (–68% and –55%, respectively) than PEP-CK (–54% and –32%, respectively) and NADP-ME (–39% and –19%, respectively) species (Tables 2, 3). Consequently, Фmax was lower in shaded NAD-ME species relative to their NADP-ME and PEP-CK counterparts (P<0.05), which indicates differential shade acclimation of photosynthetic capacity and quantum efficiency among the C4 subtypes. In control plants, the curvature (θ) was highest in NADP-ME (0.81) and lowest in NAD-ME species (0.53) (P<0.05) (Tables 2, 3). When all data were considered, Amax was well correlated with Фmax, IS, CSR, and leaf Narea (Fig. 2C–F).

Fig. 3.

The CCM efficiency parameters. (A) Photosynthetic carbon isotope discrimination (∆P) measured concurrently with leaf gas exchange, (B) carbon isotope discrimination against the ratio of intercellular [CO2] to ambient [CO2] (Ci/Ca), (C) leakiness (ϕ) at measured light (h or l), (D) ∆P measured at growth light (∆growth) against Фmax, (E) ∆DM calculated from leaf dry matter δ13C, (F) ∆P measured at growth light (∆Pgrowth) against ∆DM, and (G) and maximum quantum yield of PSII, Фmax, for C4 grasses belonging to three biochemical subtypes grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. Statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001.

The CCM efficiency paran class="Gene">meters. (A) pan> class="Disease">Photosynthetic carbon isotope discrimination (∆P) measured concurrently with leaf gas exchange, (B) carbon isotope discrimination against the ratio of intercellular [CO2] to ambient [CO2] (Ci/Ca), (C) leakiness (ϕ) at measured light (h or l), (D) ∆P measured at growth light (∆growth) against Фmax, (E) ∆DM calculated from leaf dry matter δ13C, (F) ∆P measured at growth light (∆Pgrowth) against ∆DM, and (G) and maximum quantum yield of PSII, Фmax, for C4 grasses belonging to three biochemical subtypes grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. Statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001.

Carbon isotope discrimination

Concurrent n class="Gene">measurepan> class="Gene">ments of 13CO2/12CO2 discrimination and leaf gas exchange showed that photosynthetic carbon isotope discrimination, ∆P, was independent of the C4 subtype at HL (Table 2). ∆P tended to be lower in NADP-ME species relative to the other two subtypes, but differences were not significant, except when compared with the control plants measured at HL (Table 2; Supplementary Table S3). For NADP-ME species, ∆P was unchanged by either LL or shade, while ∆P increased in PEP-CK and NAD-ME species in response to both LL and shade (22–37%) (Fig. 3A; Supplementary Table S3).

n class="Disease">Leakiness (ϕ) ranged betweenpan> 0.15 and 0.35 across the C4 grasses and light treatn class="Gene">ments (Fig. 3B, C). For shaded plants measured at HL, NAD-ME species had higher leakiness (0.29) than NADP-ME species (0.14) (Supplemetary Table S3). Overall, NAD-ME species exhibited increased ϕ at LL and in the shade environment (Fig. 3C; Supplementary Table S3).

n class="Disease">Photosynthetic carbon isotope discrimination derived from bulk leaf δ13C vn class="Chemical">alues, ∆DM, was significantly lower in NADP-ME species relative to the other two subtypes (P<0.05) (Table 2; Supplementary Table S3). Shade increased ∆DM in NAD-ME and PEP-CK species only (+30% and +22%, respectively) (Fig. 3E; Table 2; Supplementary Table S3).

There was a strong linear relationship between photosynthetic dn class="Chemical">iscriminpan>ationpan> n class="Gene">measured at growth light, ∆growth, and ∆DM (R2=0.56) (Fig. 3F). This relationship had an x-intercept of 0.9‰, which reflects the difference between ∆growth and ∆DM due to time-integrated changes in ambient 13CO2/12CO2 and post-photosynthetic fractionation. The good fit between ∆growth and ∆DM suggests that leaf δ13C is a good predictor of ∆growth, and perhaps Ci/Ca (PWUE) for C4 grasses when changes are caused by a difference in light intensity. In addition, there was a significant, negative linear relationships between Фmax and ∆growth (R2=0.35) (Fig 3D).

Activity of photosynthetic enzymes

Control n class="Gene">NAD-ME planpan>ts had the highest leaf conpan>tenpan>t of Rubisco sites (P<0.05) (Fig. 4A; Table 2: Supplemetnary Table S4). Rubisco activation decreased significantly in NAD-ME (–40%) and PEP-CK (–22%) species, while it increased by ~15% in NADP-ME species (subtype×light P=0.07) (Fig. 4A, B; Table 2; Supplementary Table S4). Consequently, initial Rubisco activity did not differ according to the C4 subtype (P>0.05), and was reduced to a greater extent in NAD-ME relative to the PEP-CK and NADP-ME species under shade in all C4 grasses (subtype×treatment P<0.08) (Fig. 4C; Table 2; Supplementary Table S4). Soluble protein content decreased under shade by 12–67% depending on the species but not the subtype (Table 2; Supplementary Table S4).

Fig. 4.

Shade acclimation of photosynthetic enzymes in C4 subtypes. (A) Rubisco sites, (B) % Rubisco activation, (C) Initial Rubisco activity, (D) PEPC activity, (E) PEPC to initial Rubisco activity ratio, and (F) decarboxylases activity for eight C4 grasses belonging to three biochemical subtypes and grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. Statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001.

Shade acclimation of photosynthetic enzyn class="Gene">mes inpan> C4 subtypes. (A) Rubisco sites, (B) % Rubisco activation, (C) Initial Rubisco activity, (D) PEPC activity, (E) PEPC to initial Rubisco activity ratio, and (F) decarboxylases activity for eight C4 grasses belonging to three biochemical subtypes and grown in control (full sunlight; white) or shade (16% of natural sunlight; black) environments. Each column represents the mean ±SE of subtype. Statistical significance levels (t-test) for the growth condition within each subtype are shown: *P<0.05; **P<0.01; ***P<0.001.

In genern class="Chemical">al, shade reduced n class="Gene">PEPC activity by 49–84% in the C4 grasses. PEPC activity was higher in control NADP-ME plants and decreased to a lesser extent in NAD-ME (66%) than in NADP-ME (69%) and PEP-CK (65%) species (Fig. 4D; Table 2; Supplementary Table S4). Consequently, shade reduced the ratio of PEPC to initial Rubisco activity in NADP-ME (–44%) but not in PEP-CK (–3%) species, while this ratio tended to increase in NAD-ME species (+30%) (Fig. 4E; Supplementary Table S4,).

There was a significant relationship between the n class="Gene">PEPC/inpan>itin class="Chemical">al Rubisco activity ratio and ∆DM (P<0.05), and this relationship was stronger in shade (R2=0.49) than in control (R2=0.40) plants. In contrast, PEPC/initial Rubisco activity showed a weaker relationship to ∆growth (R2=0.23) irrespective of treatment and subtype.

Activities of n class="Gene">NADP-ME, n class="Gene">PEP-CK, and NAD-ME enzymes were dominant in their respective subtype; however, substantial PEP-CK activity (6–25 µmol m–2 s–1) was measured in NADP-ME and NAD-ME species (Supplementary Table S4). Shade reduced the activity of NADP-ME, PEP-CK, and NAD-ME by 35–60, 52–64, and 49–57%, respectively (P<0.05). Shade also reduced the activity of total decarboxylases by 25–64% (P<0.05); the reduction was lower in NADP-ME (42%) relative to PEP-CK (60%) and NAD-ME (65%) species (Fig. 4F; Table 2; Supplementary Table S4).

The detectability of enzyn class="Gene">me activity was corroborated by immunpan>odetectionpan> of the corresponpan>dinpan>g proteinpan> for pan> class="Chemical">all the photosynthetic enzymes assayed, except for NAD-ME where a suitable antibody was not available during this study (Fig. 5). Rubisco and PEPC proteins were detected in all species and treatments. Surprisingly, NADP-ME protein was detected in all C4 species, including NAD-ME and PEP-CK. This may be attributed to cross-reaction with a non-photosynthetic isomer of NADP-ME or NAD-ME proteins (Fig. 5). PEP-CK protein was strongly detectable in Panicum maximum and to a lesser extent in Chloris gayana, although C. gayana had the highest PEP-CK activity (Fig. 5; Supplementary Table S4). In addition, PEP-CK protein was detected in three NADP-ME species, but not in Sorghum bicolor, reflecting well the trends in PEP-CK activity (Fig. 5; Supplementary Table S4).

Fig. 5.

Immunoblot analysis of photosynthetic enzymes. Immunoblot analysis for the photosynthetic proteins Rubisco, PEPC, PEP-CK, and NADP-ME extracted from leaves of eight C4 grasses belonging to three biochemical subtypes in control (C) or shade (S) environments. Loaded volumes varied between 4 μl and 15 μl in order to normalize the protein content to a common leaf area. Because of the small gel size, a limited number of samples (8–9) was loaded on an individual gel. Finally, all immunoblots of the studied protein and species were arranged in a composite figure. For uniform visualization, gamma settings of individual images were adjusted. A protein ladder was used for individual immunoblots; for simplicity, band size is referred to numerically.

Immunoblot ann class="Chemical">alyspan> class="Chemical">is of photosynthetic enzymes. Immunoblot analysis for the photosynthetic proteins Rubisco, PEPC, PEP-CK, and NADP-ME extracted from leaves of eight C4 grasses belonging to three biochemical subtypes in control (C) or shade (S) environments. Loaded volumes varied between 4 μl and 15 μl in order to normalize the protein content to a common leaf area. Because of the small gel size, a limited number of samples (8–9) was loaded on an individual gel. Finally, all immunoblots of the studied protein and species were arranged in a composite figure. For uniform visualization, gamma settings of individual images were adjusted. A protein ladder was used for individual immunoblots; for simplicity, band size is referred to numerically.

Discussion

C4 photosynthesn class="Chemical">is pan> class="Chemical">is thought to be less plastic in response to shade than C3 photosynthesis due to its complex anatomy and biochemistry (Sage and McKown, 2006). Yet, some studies found similar photosynthetic responses to LL in C3 and C4 plants (Tazoe , 2008; Pengelly ). These studies have focused on the response of selected C4 species to short-term changes in irradiance (Tazoe ; Pengelly ; Ubierna ; Bellasio and Griffiths, 2014, b) or long-term adaptation to growth under LL (Kromdijk , 2010; Tazoe ; Bellasio and Griffiths, 2014). However, there is limited information about how LL responses differ across the C4 subtypes. Here, we present the first study comparing the short- and long-term responses to LL of C4 grasses with different biochemical subtypes. We hypothesized that (i) LL (short and long term) will compromise the CCM efficiency to a greater extent in NAD-ME than in PEP-CK or NADP-ME grasses due to a greater increase in leakiness (ϕ) in the former subtype; and (ii) shade will cause a greater photosynthetic acclimation in NAD-ME grasses than in NADP-ME and PEP-CK counterparts by virtue of their higher leaf N and Rubisco content. To evaluate these hypotheses, we grew eight C4 grasses belonging to three biochemical subtypes (NADP-ME, NAD-ME, and PEP-CK) under shade (16% sunlight) or control (full sunlight) conditions, and subsequently measured their photosynthetic characteristics under both LL and HL. Our results supported both hypotheses and demonstrated that LL compromised the CCM efficiency and photosynthetic quantum yield to a greater extent in NAD-ME relative to PEP-CK and NADP-ME species.

Low light compromised the CCM efficiency most in NAD-ME followed by PEP-CK, but not in NADP-ME grasses

For the operationn class="Chemical">al CCM, the C4 cycle must be faster thanpan> the C3 cycle (i.e. pan> class="Gene">PEPC/initial Rubisco activity ratio >1) to concentrate CO2 inside the BSCs, some of which will inevitably leak back out to the MCs. In the short term, LL may compromise CCM efficiency by affecting the activity of the C3 cycle (e.g. Rubisco) more significantly than that of the C4 cycle (e.g. PEPC) and, hence, increasing ∆P, ϕ, and Фmax. Under LL, A is low and CO2 evolved during respiration can make an important contribution to the total CO2 concentration inside the BSCs. Larger Rd/A ratios under LL can potentially lead to higher ∆P. Increased ∆P due to respiratory CO2 does not involve an energy cost for the CCM but may lead to an overestimation of ϕ independently of Фmax. Long-term acclimation to LL may act to optimize CCM efficiency by reversing the negative short-term effects of LL (Bellasio and Griffiths, 2014). Hence, we used the metrics PEPC/initial Rubisco activity, Rd/A, ϕ, and Фmax to evaluate the effects of LL during measurements and growth on the CCM efficiency of the various C4 subtypes. Consequently, increased ϕ, PEPC/initial Rubisco activity, and Rd/A can be interpreted as a less efficient photosynthetic process. Assuming that bundle sheath conductance does not change with irradiance, increased ∆P and ϕ can be interpreted as a less efficient CCM and an indication of imbalance between the C3 and C4 cycles (von Caemmerer, 2000).

Response of NADP-ME grasses to LL

In the n class="Gene">NADP-ME grasses, ∆P, ∆pan> class="Disease">DM, and ϕ were not significantly impacted by LL during either measurement or growth (Fig. 3A, C, E), suggesting that in this subtype, the co-ordination between the C3 and C4 cycles was largely maintained despite changes in the light environment. Our results are in agreement with previous reports that ∆P was insensitive to LL during the measurements for NADP-ME species (Henderson ; Kubásek ; Cousins ) as well as ∆DM being insensitive to growth under shade in NADP-ME Zea mays (Sharwood ). NADP-ME species grown under shade had lower PEPC/initial Rubisco activity (–44%) and higher Rd/A (+158% at growth light) than the control plants. Decreased PEPC/initial Rubisco activity is expected to reduce ∆P, ∆DM, and ϕ, while increased Rd/A will have the opposite effect under shade. The combined opposing effects may explain the insensitivity of ∆P, ∆DM, and ϕ in response to the shade environment. In line with this conclusion, NADP-ME species showed the lowest reduction in Фmax (–19%), and it is likely that the contribution from photorespiration was negligible in the low-O2-evolving BSC chloroplasts of NADP-ME species (Ghannoum ). Previous work describing the shade acclimation of the NADP-ME of Z. mays suggested that this species reduced the ATP cost of the CCM under shade by reducing the PEPC activity more than the C3 cycle activity, which resulted in low ϕ values (Bellasio and Griffiths, 2014). Our findings support this argument by providing direct measurements of in vitro C4 and C3 cycle enzymes as well as Фmax. This argument is also supported by the modelling approach of Wang who suggested that the NADP-ME biochemical pathway is favoured at LL. In contrast to our results, differential responses of C4 and C3 cycle enzymes were reported in earlier studies with NADP-ME species (Sugiyama ; Ward and Woolhouse, 1986; Sharwood ). This discrepancy may be related to differences in the intensity of the shade treatment used. In addition, these studies considered total (rather than initial) Rubisco activity for calculating the PEPC/Rubisco activity ratio.

It n class="Chemical">is worth notinpan>g that, inpan> additionpan> to pan> class="Gene">NADP-ME decarboxylase activity, Z. mays and Cenchrus ciliaris showed significant activity of PEP-CK decarboxylase (16–25 µmol m–2 s–1), while S. bicolor and Panicum antidotale appeared as true NADP-ME types. Without considering cytosolic resistance of BSCs to CO2, Wang suggested the possibility of higher leakiness in the C4 photosynthesis model with mixed decarboxylase pathways. This was not validated in our study. Bellasio and Griffiths (2014) also suggested that the engagement of the secondary PEP-CK pathway in an NADP-ME species enables the CCM to regulate an optimal BSC [CO2] under changing light conditions. These predictions were indirectly validated in our study. Under LL, Z. mays showed higher ∆P and ϕ but similar Фmax relative to the other two NADP-ME species, P. antidotale and S. bicolor (Supplementary Table S4). However, the link between ∆P, CCM efficiency, and PEP-CK activity as a secondary decarboxylase in NADP-ME species requires further investigation.

Response of PEP-CK and NAD-ME grasses to LL

n class="Gene">PEP-CK anpan>d pan> class="Gene">NAD-ME plants had larger ∆DM under shade relative to the control condition (Fig. 3E). Previous studies have shown similar ∆DM responses to shade across the C4 subtypes (Buchmann ; Tazoe ). In PEP-CK and NAD-ME grasses, instantaneous measurements of ∆P and ϕ increased at LL, and the difference between the light treatments was highly significant when the comparison was made between control and shade plants measured under their respective growth irradiance (Fig. 3A, C). These results indicate that LL resulted in a less efficient CCM in PEP-CK and NAD-ME grasses. Additionally, the relative increase in ϕ from HL to LL was larger for control (+60%) than shade (+12%) plants. This is in line with Tazoe and suggests that a degree of acclimation to the shade condition mitigated the negative effects of LL observed in response to short-term light changes during measurements. Our results with PEP-CK and NAD-ME grasses are in agreement with previous reports of increased ∆P and ϕ with short-term exposure to LL (Henderson ; Cousins ).

In n class="Gene">NAD-ME species, shade inpan>creased the pan> class="Gene">PEPC/initial Rubisco activity (+30%) and Rd/A (+341% at growth light) and decreased Фmax (–55%). Species of the NAD-ME subtype possess significant PSII activity in the BSC (Ghannoum ), and hence potentially high [O2]. PEP-CK species exhibited intermediate responses to shade relative to the other two subtypes. In PEP-CK species, the PEPC/initial Rubisco activity ratio was not affected by shade, but the Rd/A ratio was larger (+374%) in shade than in control plants (Supplementary Table S2). Further, the reduction of Фmax under shade was intermediate in PEP-CK species (–32%) relative to NADP-ME (–19%) and NAD-ME (–55%). We also have evidence that PEP-CK species possess significant PSII activity in BSCs (Pinto, 2015). Accordingly, ∆P, ∆DM, and ϕ increased under shade in PEP-CK species to a similar extent relative to NAD-ME counterparts (Fig. 3A, C, E). Thus, in line with the first hypothesis, our results demonstrated that LL compromised the CCM efficiency of NAD-ME species more than that of PEP-CK species, while CCM efficiency was largely maintained in NADP-ME species under LL.

Shade induced larger photosynthetic down-regulation in NAD-ME relative to NADP-ME and PEP-CK species

In the current study, shade down-regulated Ah and light-saturated photosynthesn class="Chemical">is, Amax, inpan> pan> class="Gene">NAD-ME (–68%) to a greater extent than in PEP-CK (–54%) and NADP-ME (–39%) species, indicating stronger photosynthetic acclimation to shade in the former subtype (Table 3). Shade equally reduced PEPC activity in all the C4 subtypes (–68%), while Rubisco sites and activation were more profoundly reduced in NAD-ME (–60% and –40%, respectively) relative to the PEP-CK (–48% and –22%, respectively) and NADP-ME (–47% and +15%, respectively) species (Supplementary Table S4). Similar large reductions in Rubisco content and activity (>55%) were reported in studies using C3 species (Evans, 1988). In shade-grown C4 species, inconsistent changes in Rubisco content and activity have been observed (Winter ; Ward and Woolhouse, 1986, b; Tazoe ), with an average reduction of 29% (Sage and McKown, 2006). A relevant study by Ward and Woolhouse (1986) subjecting C4-NADP-ME grasses to deep shade reported a greater reduction in Rubisco activity in species from the open habitat (34%) relative to the shade habitat (3%). Likewise, NAD-ME species generally originate from relatively more open habitats than NADP-ME and PEP-CK species (Vogel ; Hattersley, 1992; Schulze ; Liu ). In addition, similar to the C3 species, NAD-ME grasses may have a greater N flexibility by having higher leaf N relative to NADP-ME and PEP-CK counterparts.

Table 3.

Parameters derived from A–Ci and light response curves for eight C4 grasses grown under control (full sunlight) or shade (16% of natural sunlight) environments

Parameter	Treatment	Subtype			C4
		NADP-ME	PEP-CK	NAD-ME
IS at HL (µmol m–2 s–1 bar–1)	Control	0.5 ± 0.06 a	0.52 ± 0.02 a	0.62 ± 0.06 a	0.53 ± 0.03
	Shade	0.27 ± 0.03 a	0.27 ± 0.02 a	0.2 ± 0.02 a	0.25 ± 0.02
	% change	–46	–49	–77	–54
CSR at HL (µmol m–2 s–1)	Control	42 ± 1 a	45 ± 1 a	41 ± 1 a	43 ± 1
	Shade	25 ± 1 b	23 ± 1 ab	15 ± 1 a	21 ± 1
	% change	–39	–49	–64	–50
IS/CSR at HL (×103)	Control	12 ± 1 a	12 ± 0 a	15 ± 1 a	12 ± 1
	Shade	10 ± 1 a	12 ± 1 a	13 ± 1 a	12 ± 1
	% change	–12	1	–9	–6
A max (µmol m–2 s–1)	Control	53 ± 3 a	57 ± 1 a	58 ± 2 a	55 ± 1
	Shade	32 ± 2 a	26 ± 1 a	18 ± 3 a	28 ± 1
	% change	–39	–54	–68	50
Maximum quantum yield (Фmax) (mol mol–1)	Control	0.06 ± 0 a	0.07 ± 0 a	0.07 ± 0 a	0.07 ± 0
	Shade	0.05 ± 0 b	0.05 ± 0 b	0.03 ± 0 a	0.05 ± 0
	% change	–19	–32	–55	–32
Curvature (θ) of light response curve	Control	0.81 ± 0.04 b	0.57 ± 0.03 ab	0.53 ± 0.04 a	0.66 ± 0.03
	Shade	0.61 ± 0.04 a	0.64 ± 0.05 a	0.64 ± 0.05 a	0.62 ± 0.03
	% change	–25	12	19	–6

Values are means ±SE (n=3–4). The ranking (from lowest=a) of subtypes within each single row using multiple-comparison Tukey’s post-hoc test. Values followed by the same letter are not significantly different at the 5% level. Significant fold changes are shown in bold (P<0.05).

Paran class="Gene">meters derived from A–Ci and light responpan>se curves for eight C4 grasses grownpan> unpan>der conpan>trol (full sunpan>light) or shade (16% of naturn class="Chemical">al sunlight) environments

Vn class="Chemical">alues are n class="Gene">means ±SE (n=3–4). The ranking (from lowest=a) of subtypes within each single row using multiple-comparison Tukey’s post-hoc test. Values followed by the same letter are not significantly different at the 5% level. Significant fold changes are shown in bold (P<0.05).

Reduced Rubn class="Chemical">isco conpan>tenpan>t pan> class="Chemical">is a common photosynthetic acclimation response to shade allowing optimal nitrogen allocation for maximal light harvesting (Boardman, 1977; Hikosaka and Terashima, 1995; Evans and Poorter, 2001; Walters, 2005). Consequently, lower Rubisco activity and activation may indicate a shift in photosynthetic limitation from Rubisco (sun leaves) to electron transport (shade leaves) (Evans, 1988; Evans and Poorter, 2001). Under shade, NAD-ME species had lower Фmax relative to NADP-ME and PEP-CK counterparts (Fig. 3). This difference may be attributed to a greater inefficiency of the NAD-ME CCM, especially under shade as argued above. It could also be attributed to inherent inefficiencies of the light conversion apparatus in the NAD-ME subtype due to the burden of operating two fully fledged linear electron transport systems with granal chloroplasts in both MCs and BSCs. This is not the case for the NADP-ME subtype, and somewhat intermediate for the PEP-CK subtype (Ghannoum , 2011). Taken together, these findings support our second hypothesis stating that larger photosynthetic reduction and acclimation in NAD-ME species is associated with their lower Rubisco activation and lower quantum efficiency relative to PEP-CK and NADP-ME species.

Whole-plant implications of differential shade acclimation among the C4 subtypes

In the current study, n class="Chemical">CO2 assimilationpan> at growth light was equpan> class="Chemical">ally reduced in NAD-ME (–81%), PEP-CK (–79%), and NADP-ME (–76%) species. However, total leaf area and plant DM were more profoundly reduced in NAD-ME (–92% and –95%, respectively) than in PEP-CK (–81% and –98%, respectively) and NADP-ME (–73% and –81%, respectively) species. In addition to reduced leaf area, the larger reduction in plant DM for NAD-ME and PEP-CK species could also be attributed to reduced CCM efficiency and Фmax. Further, the Rd/A ratio increased to a greater extent in NAD-ME and PEP-CK (~3.5-fold) than in NADP-ME species (1.6-fold) under shade, which may result in a greater C loss in these two subtypes. Taken together, these findings suggest that shade may favour NADP-ME species due to their efficient CCM and quantum yield, and lower photosynthetic down-regulation and lower increase in Rd/A relative to NAD-ME and PEP-CK species.

Thn class="Chemical">is conpan>clusionpan> pan> class="Chemical">is supported by ecological observations. NAD-ME species are preferentially found in open and arid habitats relative to the other two C4 subtypes (Osmond ; Vogel ; Hattersley, 1992; Schulze ; Liu ). On the one hand, most of the understorey C4 grasses belong to the NADP-ME subtypes, such as Setaria species (Schulze ), Paspalum species (Ward and Woolhouse, 1986; Klink and Joly, 1989; Firth ), and Microstegium vimineum (Barden, 1987). Moreover, NADP-ME species form dense canopy crops such as maize, Sorghum, Miscanthus, and sugarcane where most leaves are shaded (Sage, 2014).

It should be noted that a different light spectrum affects CCM efficiency in C4 photosynthesn class="Chemical">is (Sunpan> ). The light spectrum may vary inpan> naturpan> class="Chemical">al shade settings due to growth season, canopy compositions, and architecture (Ross ; Messier ). Therefore, an interaction effect between subtype and light spectral composition cannot be ignored, and further investigations are warranted.

Conclusion

Using C4 grass from three biochemicn class="Chemical">al subtypes anpan>d grownpan> unpan>der full sunpan>light anpan>d shade (16% of full sunpan>light) conpan>ditionpan>s equivpan> class="Chemical">alent to the light environment prevailing in lower crop canopies or forest understorey, this study demonstrated that NAD-ME and to a lesser extent PEP-CK species were generally outperformed by NADP-ME species under shade. This response was underpinned by a more efficient CCM and quantum yield in NADP-ME. These findings were corroborated by in vivo and in vitro measurements of C3 and C4 cycle enzymes, maximum quantum yield of PSII (Фmax), photosynthetic carbon isotope discrimination (ΔP), leaf dry matter δ13C, and total plant dry mass. Future research is needed to quantify the impact of respiration and photorespiration on carbon isotope discrimination (∆P) in the three biochemical subtypes of C4 photosynthesis, as well as the significance of the secondary PEP-CK decarboxylase on photosynthetic responses to shade.

Supplementary data

Supplen class="Gene">mentary data are available at JXB onpan>linpan>e.

Table S1. Summary of plant growth paran class="Gene">meters.

Table S2. Summary of gas exchange paran class="Gene">meters.

Table S3. Summary of n class="Chemical">carbon n class="Disease">isotope discrimination parameters.

Table S4. Summary of biochemicn class="Chemical">al parapan> class="Gene">meters.

Table S5. Definitions and units for variables described in the text.

Fig. S1. n class="Chemical">Glasshouse growth conditions.

Fig. S2. Photosynthetic n class="Chemical">CO2 responpan>se curves (A–Ci) of C4 grasses.

Fig. S3. Photosynthetic light response curves for C4 grasses.

Fig. S4. Sensitivity of n class="Disease">leakiness at low light

Appendix S1. n class="Disease">Leakiness calculations at low light

Click here for additionn class="Chemical">al data file.

Click here for additionn class="Chemical">al data file.

Click here for additionn class="Chemical">al data file.