Carbon Isotope Fractionation during Photorespiration and Carboxylation in Senecio1[W][OA] Gary J. Lanigan2, Nicholas Betson3, Howard Griffiths, and Ulli Seibt4* Physiological Ecology Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, United Kingdom The magnitude of fractionation during photorespiration and the effect on net photosynthetic 13C discrimination (D) were investigated for three Senecio species, S. squalidus, S. cineraria, and S. greyii. We determined the contributions of different processes during photosynthesis to D by comparing observations (Dobs) with discrimination predicted from gas-exchange measurements (Dpred). Photorespiration rates were manipulated by altering the O2 partial pressure (pO2) in the air surrounding the leaves. Contributions from 13C-depleted photorespiratory CO2 were largest at high pO2. The parameters for photorespiratory fractionation (f ), net fractionation during carboxylation by Rubisco and phosphoenolpyruvate carboxylase (b), and mesophyll conductance (gi) were determined simultaneously for all measurements. Instead of using Dobs data to obtain gi and f successively, which requires that b is known, we treated b, f, and gi as unknowns. We propose this as an alternative approach to analyze measurements under field conditions when b and gi are not known or cannot be determined in separate experiments. Good agreement between modeled and observed D was achieved with f 5 11.6& 6 1.5&, b 5 26.0& 6 0.3&, and gi of 0.27 6 0.01, 0.25 6 0.01, and 0.22 6 0.01 mol m22 s21 for S. squalidus, S. cineraria, and S. greyii, respectively. We estimate that photorespiratory fractionation decreases D by about 1.2& on average under field conditions. In addition, diurnal changes in D are likely to reflect variations in photorespiration even at the canopy level. Our results emphasize that the effects of photorespiration must be taken into account when partitioning net CO2 exchange of ecosystems into gross fluxes of photosynthesis and respiration.
Development of the theory linking the d13C signatures of plant CO2 fluxes or organic material to leaf gas exchange (Farquhar et al., 1982) has led to a wide range of applications for crops and natural vegetation. For example, d13C data are used to study plant water use efficiency (Hobbie and Colpaert, 2004; Cernusak et al., 2008; Seibt et al., 2008) and respiration and secondary fractionation processes (Ghashghaie et al., 2003; Wingate et al., 2007; Bathellier et al., 2008) and to partition net ecosystem CO2 fluxes between photosynthesis and respiration (Bowling et al., 2001; Oge´e et al., 1 This work was supported by the European Research Training Network (Network for Ecophysiology in Closing Terrestrial Carbon Budget; contract no. HPRN–CT–1999–00059), by a Marie Curie Fellowship of the European Commission to U.S. (contract no. MOIF–CT–2004–2704), and by the Department of Plant Sciences, University of Cambridge. 2 Present address: Teagasc, Johnstown Castle Environmental Research Centre, Wexford, Ireland. 3 Present address: RPS Group, Willowmere House, Compass Point Business Park, Stocks Bridge Way, St. Ives PE27 6JL, United Kingdom. 4 Present address: UMR Bioemco, 78850 Thiverval-Grignon, Universite´ Pierre et Marie Curie, Paris 6, France. * Corresponding author; e-mail [email protected]
The author responsible for the distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Ulli Seibt ([email protected]
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2003; Zobitz et al., 2007). These applications require robust estimates of net 13C discrimination (D) during photosynthesis. In C3 species, leaf level D during photosynthetic gas exchange primarily reflects the balance between CO2 supply by diffusion through stomata and CO2 demand by biochemical reactions in chloroplasts, most importantly catalysis by Rubisco (Farquhar et al., 1982). Both processes discriminate against the heavier isotope, but the fractionation during carboxylation by Rubisco (b3 ; 29&; O’Leary, 1984; Guy et al., 1993; McNevin et al., 2006) is much larger than that during CO2 diffusion through stomata (a ; 4.4&; Craig, 1953). Measurements of D can thus offer insights into the interplay between stomatal conductance and carbon assimilation of leaves. But additional processes also affect net D values: leaf boundary layer diffusion, internal (mesophyll) diffusion, photorespiration, and day respiration. Integrating all contributions, net 13C discrimination can be calculated (Farquhar et al., 1982; Wingate et al., 2007) as: Ca 2 Cs Cs 2 Ci Ci 2 Cc 1a 1 am Ca Ca Ca Cc G Rd Cc 2 G 1b 2f 2e Ca Ca ðA 1 Rd Þ Ca
D 5 ab
where Ca, Cs, Ci, and Cc are the CO2 mole fractions in ambient air, at the leaf surface, in the intercellular air space, and at the sites of carboxylation, respectively, G* is the compensation point in the absence of dark respiration, and Rd is the rate of day respiration. In addition to stomatal diffusion (a) and carboxylation (b), there are fractionations associated with CO2 diffusion through
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the leaf boundary layer (ab ; 2.9&) and mesophyll (am, consisting of CO2 dissolution [1.1&; Vogel, 1980] and liquid phase diffusion [0.7&; O’Leary, 1984]) into the chloroplasts, as well as photorespiration (f) and day respiration (e). A full list of symbols and abbreviations is given in Supplemental Table S1. Several of these processes are still major sources of uncertainty for estimating D. For example, there is no consensus on the fractionation factors during photorespiration (f) and day respiration (e), which can amplify diurnal patterns in D (Wingate et al., 2007). The net fractionation during carboxylation (b) may be lower than that of Rubisco (b3 ; 29&) due to contributions from phosphoenolpyruvate carboxylase (PEPc; b4 ; 25.7&; O’Leary et al., 1991). In addition, the mesophyll conductance (gi) of leaves needs to be determined to calculate Cc, the CO2 mole fraction at the sites of carboxylation [A 5 gi(Ci 2 Cc)]. For photorespiration, f values of 7& (Rooney, 1988), 8& (Gillon, 1997), and 10& to 14& (Igamberdiev et al., 2004) have been reported from a limited number of in vivo experiments on intact leaves, with 11& expected from theory (Tcherkez, 2006). Here, we present new in vivo estimates of the fractionation factor associated with photorespiration (f) and the net fractionation during carboxylation (b), determined from leaf level D measurements for three species in the genus Senecio, with contrasting leaf morphology, photosynthetic rates, and stomatal sensitivities. Photorespiration rates were manipulated by varying the O2 partial pressure (pO2) during the experiments. The parameters f, b, and gi were treated as unknowns and determined simultaneously for all measurements. We propose this as an alternative approach to analyze measurements under field conditions when b and gi are not known or cannot be determined in separate experiments.
lower G* (compensation point in the absence of dark respiration, derived from A/Ci curves) at low pO2 due to reduced rates of oxygenation. Day respiration rates (Rd) were generally low and showed little effect of pO2. In addition, gas-exchange and leaf variables exhibited systematic differences between the species. S. squalidus had the lowest specific leaf mass, G*, and Rd and the highest photosynthetic capacity and stomatal conductance, whereas S. greyii had the highest specific leaf mass, G*, and Rd and the lowest photosynthetic capacity. Net Photosynthetic 13C Discrimination and Photorespiratory Fractionation
At all pO2 levels, S. squalidus and S. cineraria had higher Dobs values (calculated using Eq. 5 below) than S. greyii (Fig. 1). In a qualitative comparison at similar Ci/Ca ratios, Dobs measured under nonphotorespiratory conditions (20 mbar pO2) was 1& to 2& higher than at typical atmospheric oxygen concentrations (210 mbar pO2), illustrating the decrease in Dobs due to isotopically depleted CO2 released during photorespiration. Except for S. greyii, this offset increased further at 300 mbar pO2. For all Dobs measurements, Dpred was calculated from gas-exchange data using Equation 1. Mesophyll conductance (gi) and the fractionation factors b and f were treated as unknowns. A range of values was tested for these parameters: 0.1 to 0.3 mmol m22 s21 for gi, 20& to 30& for b, and 0& to 20& for f. In addition, all calculations were repeated for values of 26&, 0&, and 16& for e. For each parameter combination, Dpred was calculated for all data points, and a least absolute deviations regression was performed for Dpred versus Dobs. The resulting regression parameters (slope, intercept, and mean absolute deviation) are presented in Figure 2 for a range of combinations of b and f, using e 5 0& and the best fit gi values (see below). Figure 2 illustrates that varying b mainly affects the slope of the Dpred versus Dobs regression, whereas f mainly affects the intercept. We then determined the combinations that led to the best agreement between Dpred and Dobs for all pO2 conditions (i.e. the parameter set [b, f, and gi] that produced a regression with a slope of 1 and an intercept of 0; Fig. 3). This was achieved for f 5 11.6&, b 5 26.0&,
RESULTS Leaf Physiology and Gas-Exchange Characteristics
Patterns in gas-exchange characteristics common to all species (Table I) included higher maximum rates of photosynthesis, higher stomatal conductance, and
Table I. Characteristics of three Senecio species measured at different pO2 levels Species
Specific Leaf Mass gm
mmol NADH mg21 protein s21
mmol m22 s21
20 210 300 20 210 300 20 210 300
2.7 38 60 4.0 41 70 4.1 45 77
20.6 14.8 9.9 16.8 12.4 6.7 11.0 8.4 5.1
0.30 6 0.05
0.16 6 0.05
0.60 6 0.20
gi mol m
0.57 0.44 0.40 0.46 0.38 0.31 0.19 0.17 0.10
Rd mmol m22 s21
0.12 0.14 0.15 0.20 0.20 0.22 0.41 0.38 0.39
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during photosynthesis. In particular, leaf level measurements of gas exchange and D were used to determine the fractionation factor f for photorespiration in vivo under controlled laboratory conditions. Keeping everything else constant, different rates of photorespiration were achieved in our experiments by varying the oxygen partial pressure in the air surrounding the leaves. At low pO2, the decreased oxygenase activity (as indicated by smaller G*; Table I) was manifested in 1& to 2& higher Dobs at similar Ci/Ca compared with ambient or elevated pO2 conditions (Fig. 1). The simultaneous effects of different processes on D cannot be separated easily, because D contains several unknown parameters: the fractionation factors b, f, and e and mesophyll conductance, gi. This problem is often addressed successively: gi is derived using a prescribed value of b (usually 29&), and the residual is then assumed to reflect the contribution from photorespiration. A commonly used method to derive gi is based on a regression of Di 2 Dobs versus A/Ca (Evans et al., 1986), where Di is the predicted value assuming Cc 5 Ci (i.e. no resistance to CO2 transfer during internal [mesophyll] diffusion to the sites of carboxylation): Di 5 a
Ca 2 Ci Ci 1 b# Ca Ca
Assuming that Equation 1 reflects Dobs (neglecting boundary layer effects for simplicity) and using A 5 gi (Ci 2 Cc), combining Equations 1 and 2 yields:
Figure 1. Net 13C discrimination, Dobs, against the ratio of intercellular to ambient CO2 mole fraction (Ci/Ca) for S. squalidus (A), S. cineraria (B), and S. greyii (C) measured at 20, 210, and 300 mbar pO2.
and gi values of 0.27, 0.25, and 0.22 mmol m22 s21 for S. squalidus, S. cineraria, and S. greyii, respectively (Fig. 3), yielding a robust correlation (r2 5 0.91) and small absolute deviation (0.72) between Dpred and Dobs values for all species and conditions combined. For leaves assimilating carbon at a temperature of 21.4°C (Helliker and Richter, 2008), neglecting f would lead to overestimation of D by 1.2& compared with our best fit estimate of f 5 11.6&. Applying the commonly used value of f 5 8& would result in a small but detectable overestimation by 0.4& compared with our estimate of f.
This article attempts to quantify the contributions from different processes on net 13C discrimination Plant Physiol. Vol. 148, 2008
Figure 2. Regression parameters for Dobs and Dpred calculated from Equation 1 for a range of combinations of b and f (using e 5 0&). The plot contains the slopes of the regression (red horizontal lines), their intercepts (dark blue vertical lines), and the mean absolute deviation (gray concentric ovals) between Dobs and Dpred. The best fit parameters are found at the minimum of the mean absolute deviation ‘‘valley’’ where the 0 intercept and slope of 1 lines cross. 2015
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Rd Ca ðA 1 Rd Þ A 1 ðb# 2 bÞ ðDi 2 Dobs Þ 5 gi Ci Ci G Rd Cc 2 G 1f 1e ð4Þ Ci ðA 1 Rd Þ Ci b 2 am 2 e
Figure 3. The correlation between Dobs and Dpred for the best fit parameters (b 5 26.0&, f 5 11.6&) using e 5 0&. The solid line denotes the 1:1 correlation.
Rd G ðA 1 Rd Þ A Di 2 Dobs 5 1f gi Ca Ca Rd Cc 2 G 1e ðA 1 Rd Þ Ca b 2 am 2 e
However, this approach requires that the value of b is known and that the contributions from respiratory terms do not change in a systematic way (with A). Otherwise, any errors in the estimate of b are propagated into errors in gi and affect subsequent calculations, such as the solution for f. Alternatively, the difference between the actual value of b and that assumed in Equation 2 (b#) can be estimated from the y intercept of (Di 2 Dobs)Ca/Ci against A/Ci (von Caemmerer and Evans, 1991):
But this requires that the contributions from photorespiration and day respiration can be neglected, which is often not valid, particularly under field conditions or in our experiments specifically designed to produce a wide range of photorespiratory contributions. Instead, we avoided any interference from propagated errors by identifying the best fit for all parameters simultaneously. We based our analysis on the assumption that the three Senecio species may differ in mesophyll conductance but that the same fractionation factors (b, f, and e) could be applied to all of them. Combining data from all experiments, we determined a photorespiratory fractionation factor f of 11.6& 6 1.5&. (Note that a preliminary version of this data set was presented in Table II and Fig. 6 of Ghashghaie et al. , with f reported as 9& and 11&.) Our new value is larger than previous in vivo estimates (Table II) on intact leaves of 6.2& 6 0.5&, 7.4& 6 0.3& (Rooney, 1988), and 8& (Gillon, 1997; revised from 0.5& and 3.3& [Gillon and Griffiths, 1997]). The experiments of Rooney (1988) were carried out at the CO2 compensation point (G), where photosynthetic CO2 uptake is balanced by respiratory CO2 releases. If the isotopic fluxes are at steady state, all diffusional fractionations cancel. An additional assumption was that there is no day respiration (i.e. G 5 G*), so that Ca 5 Cs 5 Ci 5 Cc 5 G*, and Equation 1 can be simplified to D 5 b – f. In two experiments, D was determined as 22.6& and 21.4& from the isotopic composition of chamber air and leaf material, yielding f 5 6.4& and 7.6& for b 5 29&, with f again depending on the choice of b. If day respiration is included (G . G*), then Ca 5 Cs 5 Ci 5 Cc 5 G, and the above equation changes to D 5 b – f G*/G – e(1 – G*/G). The
Table II. Estimates of the fractionation factors during photorespiration (f) and Gly decarboxylation (g)a Estimate
Theoretical In vitro (mitochondria) In vivo
Pisum sativum, Spinacia oleracea Glycine max
15 to 20 22 216 to 18
Triticum aestivum, Phaseolus vulgaris Hordeum vulgare, Arabidopsis thaliana, Solanum tuberosum S. squalidus, S. cineraria, S. greyii a
f ; g/2 (Rooney, 1988; Tcherkez, 2006).
7.5 to 10 11
Abell and O’Leary (1988) Tcherkez (2006) Ivlev et al. (1996)
6.2, 7.4 9.8, 11.4
Rooney (1988) Rooney (1988), recalculated including Rd Gillon (1997)b
8 9.8 to 13.7
Igamberdiev et al. (2004)
11.6 6 1.5
Revised from Gillon and Griffiths (1997). Plant Physiol. Vol. 148, 2008
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equation now reflects the relative contributions from photorespiration and day respiration to total respiratory fluxes, even if there is no fractionation during day respiration (e 5 0). With a rough estimate of 0.73 for G*/G (calculated from Farquhar et al. , using Vcmax ; 50 mmol m22 s21 and Rd ; 0.7 mmol m22 s21, with Rd/Rn ; 0.3 at 140 mL L21 CO2 [Tcherkez et al., 2008], where Rn [;1 mmol m22 s21] is the nighttime respiration rate), the resulting f for the experiments of Rooney (1988) would be larger: 8.7& and 10.3& for e 5 0 and 10.9& and 12.5& for e 5 26&, very close to our estimate of 11.6& 6 1.5&. Our estimate is also similar to recent results of 10& to 14& (Igamberdiev et al., 2004). In these experiments, photorespiration was manipulated through imposed stress (e.g. drought) and photorespiratory mutants, which may have affected other metabolic processes and complicated the identification of f itself. Glycine decarboxylase (GDC), the enzyme responsible for CO2 release during photorespiration, discriminates against 13C, with the resultant photorespired CO2 depleted in 13C. GDC is a multienzyme complex consisting of four enzymes and requires pyridoxal phosphate as a cofactor (Walker and Oliver, 1986; Rooney, 1988). Because of similar reaction mechanisms, the fractionation during Gly decarboxylation (g) was expected to be in the same range as other pyridoxal phosphate-dependent decarboxylases, 15& to 20& (Abell and O’Leary, 1988; Rooney, 1988). As half of the substrate of GDC is converted to product (CO2), f should be 7.5& to 10& at a steady-state flux of carbon through the pathway if Gly has the same isotopic composition as current photoassimilates. Recent theoretical estimates for g were 22&, yielding f on the order of 11& (Tcherkez et al., 2005; Tcherkez, 2006), very close to the value of f observed in our study. Theory predicts interactions between f and e, but these are minor across the range of plausible f values (Tcherkez, 2006). The in vitro estimates of g for different C3 species (Table II) span a large range of 216& to 18& (Ivlev et al., 1996; Igamberdiev et al., 2001; Ivlev, 2001). However, these results cannot easily be related to f. The measurements were performed on purified enzymes or isolated mitochondria at a range of pH values and with various cofactors (e.g. NAD1 and ADP) added to the reaction. As it is not known which of these experimental setups best reflects the conditions in a living cell, the in vitro estimates can only give a range of possible g values, not the most likely value for f in actively photosynthesizing cells. We obtained a value of 26& for b, the net fractionation during carboxylation, lower than previous estimates of 27& to 32& (von Caemmerer and Evans, 1991). In vitro determinations of Rubisco fractionation (b3) have yielded values of 27& to 31& (Roeske and O’Leary, 1984; Guy et al., 1993; McNevin et al., 2006), but the net value of b can be lower due to contributions from PEPc carboxylation (b4). It is also possible that b3 itself is smaller in some species. For our experiments on the three Senecio species, differences in net b values Plant Physiol. Vol. 148, 2008
were not evident in their Dobs data. Based on in vitro estimates of enzyme activity, S. greyii had the highest extractable PEPc activity (Table I) and the lowest maximum photosynthetic rate (Amax), reflecting Rubisco activity. As PEPc discrimination has the opposite sign from that of Rubisco, S. greyii, with the highest PEPc:Amax, could have a lower b than S. squalidus (PEPc:Amax smaller by a factor of 4). However, the Dobs data of S. greyii and S. squalidus had almost identical slopes (Fig. 1), and Dpred versus Dobs fits well with a single b value (Fig. 3). Thus, extractable PEPc activity assayed in vitro does not appear to be a reliable indicator of the in vivo PEPc metabolic flux and its influence on b, the net discrimination during carboxylation. Because many parameter combinations gave a 1:1 slope and an intercept of 0 for Dpred versus Dobs, the mean absolute deviation was an important criterion in determining the best fit parameters. For example, assuming b 5 29&, a 1:1 fit could be achieved for f 5 5& and gi 5 0.14, 0.13, and 0.11 mol m22 s21 (for S. squalidus, S. cineraria, and S. greyii, respectively), but the mean absolute deviation of 1.8& was more than twice that of the best fit parameters (0.7&). Nevertheless, a range of parameter combinations gave almost equally good agreement between Dpred and Dobs. Specifically, all gi values had a range of 60.01 mol m22 s21 with similar regression parameters as the best fit parameters reported above. In most cases, the two herbaceous species, S. squalidus and S. cineraria, had higher gi than the woody species with the thickest leaves, S. greyii, as expected (Warren and Adams, 2006). Within the 0.01 range, the value obtained for b was not sensitive to changes in gi, but the resulting value of f changed by up to 1.5& depending on the gi used. To take this uncertainty into account, we report the value of f for our study as 11.6& 6 1.5&. Our analysis method is particularly useful for field measurements, in which experimental conditions cannot be as carefully controlled as in the laboratory. On the other hand, we propose that the contributions from different processes to net D can be identified best by combining Dobs data with independent measurements of b and gi (through Dobs at low O2 and fluorescence) in controlled laboratory studies. Our results were not sensitive to the value chosen for e, the fractionation during day respiration. Repeating our analysis for e values of 16& and 26& (Duranceau et al., 1999; Ghashghaie et al., 2003) did not have an effect on the resulting b value and changed the resulting f by less than 0.5&. The value of e for use in Equation 1 has not been established yet. Respiratory CO2 signals reflect the partitioning between starch and sugars (Nogue´s et al., 2004; Tcherkez and Farquhar, 2005). Additional minor complications can arise from variations in gi (for review, see Flexas et al., 2008) or changes in the substrate used for day respiration, for example, due to mitochondrial respiration mobilizing older carbon pools (Ghashghaie et al., 2001, 2003; Tcherkez et al., 2003, 2005; Gessler et al., 2008), 2017
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particularly at low assimilation rates (Wingate et al., 2007). Neglecting photorespiratory fractionation would lead to an overestimation by 1.2& in the mean assimilation weighted D for leaves at temperatures of 21.4°C (Helliker and Richter, 2008), but the deviation can be larger in arid and tropical ecosystems or during periods of higher temperatures in any ecosystem. Diurnal changes in D are likely to reflect variations in photorespiration even at the canopy level. For example, photorespiratory contributions can have a large increase between the typically lower morning temperatures (0.9& at 15°C) and higher midday temperatures (2& at 35°C). Thus, reliable f values are required to derive accurate estimates of D at the canopy scale and reduce the uncertainty associated with isotopic partitioning of net CO2 fluxes. At the same time, the amount of structural carbon laid down at times of enhanced photorespiration (drought, high temperature, or salinity; for review, see Wingler et al., 2000) should be minimal. However, relative rates of photorespiration would have been generally higher during periods of low atmospheric CO2, such as the last glacial maximum or even in the preindustrial atmosphere compared with today’s atmosphere. For example, the contribution of photorespiration to net D would increase to 1.6& at 280 mmol mol21 and to 2.5& at 180 mmol mol21 atmospheric CO2 mole fraction, suggesting small but detectable effects of changing photorespiratory contributions on d13Cplant (Seibt et al., 2008). CONCLUSION
We have demonstrated the effects of fractionation during photorespiration on net D at the leaf level. Photorespiratory fractionation was observed as a decrease in Dobs at high pO2, resulting from the release of isotopically lighter CO2 during the Gly decarboxylase reaction. From concurrent measurements of Dobs and gas exchange, we determined the in vivo value of f, the photorespiratory fractionation factor, as 11.6&, higher than previous estimates (Rooney, 1988; Gillon, 1997) but similar to theoretical predictions (Tcherkez, 2006). Mesophyll conductance (gi) and fractionation factors (b and f) were determined simultaneously to avoid propagating errors in b or gi estimates into subsequent calculations. Our results confirm that photorespiration is an important component of the net photosynthetic discrimination of C3 plants. Photorespiratory effects on D should be taken into account to partition net ecosystem exchange into gross CO2 fluxes at the canopy scale.
MATERIALS AND METHODS Plant Material Three species of the genus Senecio were studied: (1) S. squalidus (Oxford ragwort), a fast-growing, short-lived annual herb; (2) S. cineraria, a slower
growing, annual/biennial herb with thick hairy leaves; and (3) S. greyii, a slow-growing shrub with thick hairy leaves. S. squalidus was grown from seeds collected from specimens grown in the Botanic Gardens at the University of Cambridge and soaked overnight. Postgermination, plants were transplanted into 8-cm pots containing John Innes No. 2 compost and grown in an air-conditioned, naturally lit greenhouse for 3 weeks prior to experiments. S. cineraria and S. greyii plants were purchased at 2 weeks and 6 months age, respectively (from Ansells Nurseries). They were transplanted into 8-cm and 30-cm pots containing John Innes No. 2 compost and grown in the same greenhouse as the S. squalidus specimens for 2 months prior to experimentation.
Gas-Exchange Measurements Gas-exchange measurements were made on the youngest fully expanded leaves using an infrared gas analyzer (CIRAS-1; PP Systems) with a 10-cm2 Parkinson leaf chamber illuminated by a Walz fiber-optic lighting unit (Fiber Illuminator FL-440 and Special Fibreoptics 400-F; Walz). Compressed air (d13C 5 210.9&) containing O2 at partial pressures of 30, 210, and 300 mbar (BOC Special Gases) and CO2 at 370 mbar were used to supply air to the chamber, bubbled through a saturated solution of NaCl at 25°C to achieve relative humidity of approximately 80%. Light response curves were performed to estimate the maximum photosynthetic rate (Amax). CO2 response (A/Ci) curves were carried out on four plants at each pO2 and light levels of 100, 300, and 1,000 mmol m22 s21 to obtain the compensation point in the absence of dark respiration (G*) and day respiration (Rd; Brooks and Farquhar, 1985).
Attached leaves were placed in the leaf chamber and acclimated to the chamber conditions for 20 min. Flow rates were maintained at 250 mL min21 to obtain large CO2 depletions across the chamber. A range of Ci/Ca values was achieved by measuring each leaf at high and low light (900 and 250 mmol m22 s21). Four plants were sampled for each species, and measurements at all three pO2 levels were performed on the same leaf. The CO2 in the air exiting the chamber was trapped cryogenically (for detailed description, see Broadmeadow et al., 1992). Briefly, air from downstream of the cuvette (analysis gas) was passed at positive pressure to a glass collection line at a rate of 150 mL min21 via a needle valve. The CO2 was trapped by passing the air through a cold trap submerged in liquid N2 at a pressure of less than 0.6 kPa. The line was then isolated and evacuated to 1023 kPa, after which the CO2 was liberated from the cold trap in acetone at 280°C to retain water vapor. The CO2 was then drawn into a removable vial, which was sealed with a butane gas torch. Gas-exchange parameters were recorded on the infrared gas analyzer before and after CO2 collection, with the mean of both readings used in the analyses. Reference gas was collected at the start of each experimentation day and after every fourth sample collection. The samples of analysis and reference gas were purified via two further cryodistillations (Borland et al., 1993) and analyzed on a VG-903 dual-inlet triple collector mass spectrometer (modified by Provac Services). The 13C/12C ratios of the samples were determined against those of reference CO2 (d13C 5 242.5&; BDH) and reported with respect to the PeeDee Belemnite standard. Defining net photosynthetic discrimination as D 5 Ra =Rp – 1, where Ra and Rp are the isotope ratios of atmospheric CO2 and the product (e.g. photoassimilates), the observed 13C discrimination in a leaf cuvette during photosynthesis (Dobs) was determined following Evans et al. (1986) from: 13
jðd Co 2 d Ce Þ 1 1 d13 Co 2 jðd13 Co 2 d13 Ce Þ
where j 5 Ce/(Ce – Co), and Ce and Co, d13Ce and d13Co refer to the mole fractions and isotope ratios of CO2 in air entering and exiting the leaf cuvette, respectively.
Determination of PEPc Activity Frozen leaf tissue (200 mg) was extracted at 4°C in 2 mL of buffer containing 200 mM Tris base (pH 8), 2 mM EDTA, 2% polyethylene glycol 20,000, 1 mM dithiothrietol, 1 mM benzamidine, 10 mM malate, and 350 mM NaHCO3. Samples were centrifuged at 12,000g for 3 min, and the supernatant was desalted on a Sephadex G-25 column. PEPc activity was measured as the oxidation of NADH in the presence of PEP, malate dehydrogenase, and total leaf protein (Chu et al., 1990). Briefly, NADH consumption was measured over
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6 min at 340 nm using a UV-300 spectrophotometer (Spectronic Unicam), with the reaction initiated by the addition of 100 mL of extract to 850 mL of assay cocktail (65 mM Tris base [pH 7.8], 0.2 mM NADH, 10 mM NaHCO3, and 5 mM MgCl2) with 2 mM PEP. Total soluble protein content of extracts was obtained by mixing 10 mL of protein extract with 90 mL of water and 4 mL of Bradford reagent (Bradford, 1976). The sample was precipitated for 15 min and the A595 was measured. Protein content was calibrated across a range of 0 to 100 mg using a 1-mg stock of bovine serum albumin in water.
Supplemental Data The following materials are available in the online version of this article. Supplemental Table S1. List of abbreviations and symbols used in the text.
ACKNOWLEDGMENTS We thank Barney Davies for his help with the PEPc protocol. We are grateful to Glynn Jones for technical assistance with isotope ratio mass spectroscopy. We thank Guillaume Tcherkez, Jaleh Ghashghaie, and Graham Farquhar for valuable discussions and the anonymous reviewers for their helpful comments on this and an earlier version of the manuscript. Received September 20, 2008; accepted October 12, 2008; published October 15, 2008.
LITERATURE CITED Abell LM, O’Leary MH (1988) Isotope effect studies of the pyridoxal 5#-phosphate dependent histidine decarboxylase from Morganella morganni. Biochemistry 27: 5927–5933 Bathellier C, Badeck FW, Couzi P, Harscoe¨t S, Mauve C, Ghashghaie J (2008) Divergence in d13C of dark respired CO2 and bulk organic matter occurs during the transition between heterotrophy and autotrophy in Phaseolus vulgaris plants. New Phytol 177: 406–418 Borland AM, Griffiths H, Broadmeadow MSJ, Fordham MC, Maxwell C (1993) Short-term changes in carbon-isotope discrimination in the C3-CAM intermediate Clusia minor L. growing in Trinidad. Oecologia 95: 444–453 Bowling DR, Tans PP, Monson RK (2001) Partitioning net ecosystem carbon exchange with isotopic fluxes of CO2. Glob Change Biol 7: 127–145 Bradford MM (1976) A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72: 248–254 Broadmeadow MSJ, Griffiths H, Maxwell C, Borland AM (1992) The carbon isotope ratio of plant organic material reflects temporal and spatial variations in CO2 partial pressure and d13C within tropical forest formations in Trinidad. Oecologia 89: 435–441 Brooks A, Farquhar GD (1985) Effect of temperature on the CO2/O2 specificity of ribulose-1,5-bisphosphate carboxylase/oxygenase and the rate of respiration in the light. Planta 165: 397–406 Cernusak LA, Winter K, Aranda J, Turner BL (2008) Conifers, angiosperm trees, and lianas: growth, whole-plant water and nitrogen use efficiency, and stable isotope composition (d13C and d18O) of seedlings grown in a tropical environment. Plant Physiol 148: 642–659 Chu C, Dai Z, Ku SBM, Edwards G (1990) Induction of Crassulacean acid metabolism in the facultative halophyte Mesembryanthemum crystallinum by abscisic acid. Plant Physiol 93: 1253–1260 Craig H (1953) The geochemistry of the stable carbon isotopes. Geochim Cosmochim Acta 3: 53–92 Duranceau M, Ghashghaie J, Badeck F, Deleens E, Cornic G (1999) d13C of CO2 respired in the dark in relation to d13C of leaf carbohydrates in Phaseolus vulgaris L under progressive drought. Plant Cell Environ 22: 515–523 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. J Plant Physiol 13: 281–292 Farquhar GD, O’Leary MH, Berry JA (1982) On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. J Plant Physiol 9: 121–137 Farquhar GD, von Caemmerer S, Berry JA (1980) A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149: 78–90
Plant Physiol. Vol. 148, 2008
Flexas J, Ribas-Carbo´ M, Diaz-Espejo A, Galme´s J, Medrano H (2008) Mesophyll conductance to CO2: current knowledge and future prospects. Plant Cell Environ 31: 602–621 Gessler A, Tcherkez G, Peuke AD, Ghashghaie J, Farquhar GD (2008) Experimental evidence for diel variations of the carbon isotope composition in leaf, stem and phloem sap organic matter in Ricinus communis. Plant Cell Environ 31: 941–953 Ghashghaie J, Badeck FW, Lanigan GJ, Nogues S, Tcherkez G, Deleens E, Cornic G, Griffiths H (2003) Carbon isotope fractionation during dark respiration and photorespiration in C3 plants. Phytochem Rev 2: 145–161 Ghashghaie J, Duranceau M, Badeck FW, Cornic G, Adeline MT, Deleens E (2001) d13C of CO2 respired in the dark in relation to delta d13C of leaf metabolites: comparison between Nicotiana sylvestris and Helianthus annuus under drought. Plant Cell Environ 24: 505–515 Gillon JS (1997) Carbon isotope discrimination: interactions between respiration, leaf conductance and photosynthetic capacity. PhD thesis. University of Newcastle upon Tyne, Newcastle, UK Gillon JS, Griffiths H (1997) The influence of (photo)respiration on carbon isotope discrimination in plants. Plant Cell Environ 20: 1217–1230 Guy RD, Fogel ML, Berry JA (1993) Photosynthetic fractionation of the stable isotopes of oxygen and carbon. Plant Physiol 101: 37–47 Helliker BR, Richter SL (2008) Subtropical to boreal convergence of treeleaf temperatures. Nature 454: 511–514 Hobbie EA, Colpaert JV (2004) Nitrogen availability and mycorrhizal colonization influence water use efficiency and carbon isotope patterns in Pinus sylvestris. New Phytol 164: 515–525 Igamberdiev AU, Ivlev AA, Bykova NV, Threlkeld CN, Lea PJ, Gardestrom P (2001) Decarboxylation of glycine contributes to carbon isotope fractionation in photosynthetic organisms. Photosynth Res 67: 177–184 Igamberdiev AU, Mikkelsen TN, Ambus P, Bauwe H, Lea PJ, Gardestro¨m P (2004) Photorespiration contributes to stomatal regulation and carbon isotope fractionation: a study with barley, potato and Arabidopsis plants deficient in glycine decarboxylase. Photosynth Res 81: 139–152 Ivlev AA (2001) Carbon isotope effects (C13/C12) in biological systems. Separ Sci Tech 36: 1819–1914 Ivlev AA, Bykova NV, Igamberdiev AU (1996) Fractionation of carbon (C13/C12) isotopes in glycine decarboxylase reaction. FEBS Lett 386: 174–176 McNevin DB, Badger MR, Kane HJ, Farquhar GD (2006) Measurement of (carbon) kinetic isotope effect by Rayleigh fractionation using membrane inlet mass spectrometry for CO2-consuming reactions. Funct Plant Biol 33: 1115–1128 Nogue´s S, Tcherkez G, Cornic G, Ghashghaie J (2004) Respiratory carbon metabolism following illumination in intact French bean leaves using 13 C/12C isotope labeling. Plant Physiol 136: 3245–3254 Oge´e J, Peylin P, Ciais P, Bariac T, Brunet Y, Berbigier P, Roche C, Richard P, Bardoux G, Bonnefond JM (2003) Partitioning net ecosystem carbon exchange into net assimilation and respiration using 13CO2 measurements: a cost-effective sampling strategy. Global Biogeochem Cycles 17: 39-1–39-18 O’Leary MH (1984) Measurement of the isotopic fractionation associated with diffusion of carbon dioxide in aqueous solution. J Phys Chem 88: 823–825 O’Leary MH, Madhavan S, Paneth P (1991) Physical and chemical basis of carbon isotope fractionation in plants. Plant Cell Environ 15: 1099–1104 Roeske CA, O’Leary MH (1984) Carbon isotope effects on the enzymecatalyzed carboxylation of ribulose biphosphate. Biochemistry 23: 6275–6284 Rooney MA (1988) Short-term carbon isotope fractionation by plants. PhD thesis. University of Wisconsin, Madison, WI Seibt U, Rajabi A, Griffiths H, Berry JA (2008) Carbon isotopes and water use efficiency: sense and sensitivity. Oecologia 155: 441–454 Tcherkez G (2006) How large is the carbon isotope fractionation of the photorespiratory enzyme glycine decarboxylase? Funct Plant Biol 33: 911–920 Tcherkez G, Bligny R, Gout E, Mahe´ A, Hodges M, Cornic G (2008) Respiratory metabolism of illuminated leaves depends on CO2 and O2 conditions. Proc Natl Acad Sci USA 105: 797–802 Tcherkez G, Cornic G, Bligny R, Gout E, Ghashghaie J (2005) In vivo respiratory metabolism of illuminated leaves. Plant Physiol 138: 1596–1606 Tcherkez G, Farquhar GD (2005) Carbon isotope effect predictions for
Lanigan et al.
enzymes involved in the primary carbon metabolism of plant leaves. Funct Plant Biol 32: 277–291 Tcherkez G, Nogue´s S, Bleton J, Cornic G, Badeck FW, Ghashghaie J (2003) Metabolic origin of carbon isotope composition of leaf darkrespired CO2 in Phaseolus vulgaris L. Plant Physiol 131: 237–244 Vogel JC (1980) Fractionation of the carbon isotopes during photosynthesis. Sitzungsber Heidelb Akad Wiss 3: 111–135 von Caemmerer S, Evans JR (1991) Determination of the average partial pressure of CO2 in chloroplasts from leaves of several C3 plants. J Plant Physiol 18: 287–305 Walker JL, Oliver DJ (1986) Glycine decarboxylase multienzyme complex: purification and partial characterization from pea leaf mitochondria. J Biol Chem 261: 2214–2221
Warren CR, Adams MA (2006) Internal conductance does not scale with photosynthetic capacity: implications for carbon isotope discrimination and the economics of water and nitrogen use in photosynthesis. Plant Cell Environ 29: 192–201 Wingate L, Seibt U, Moncrieff JB, Jarvis PG, Lloyd JJ (2007) Variations in 13 C discrimination during CO2 exchange by Picea sitchensis branches in the field. Plant Cell Environ 30: 600–616 Wingler A, Lea PJ, Quick WP, Leegood RC (2000) Photorespiration, metabolic pathways and their role in stress protection. Philos Trans R Soc Lond B Biol Sci. 355: 1517–1529 Zobitz JM, Burns SP, Oge´e J, Reichstein M, Bowling DR (2007) Partitioning net ecosystem exchange of CO2: a comparison of a Bayesian/isotope approach to environmental regression methods. J Geophys Res 112: G03013
Plant Physiol. Vol. 148, 2008