Research ArticleBREAKTHROUGH TECHNOLOGIES

Novel Approach for High-Throughput Metabolic Screening of Whole Plants by Stable Isotopes

Lisa Maria Dersch, Veronique Beckers, Detlev Rasch, Guido Melzer, Christoph Bolten, Katina Kiep, Horst Becker, Oliver Ernst Bläsing, Regine Fuchs, Thomas Ehrhardt, Christoph Wittmann

Published May 2016. DOI: https://doi.org/10.1104/pp.15.01217

Abstract

Here, we demonstrate whole-plant metabolic profiling by stable isotope labeling and combustion isotope-ratio mass spectrometry for precise quantification of assimilation, translocation, and molecular reallocation of 13CO2 and 15NH4NO3. The technology was applied to rice (Oryza sativa) plants at different growth stages. For adult plants, 13CO2 labeling revealed enhanced carbon assimilation of the flag leaf from flowering to late grain-filling stage, linked to efficient translocation into the panicle. Simultaneous 13CO2 and 15NH4NO3 labeling with hydroponically grown seedlings was used to quantify the relative distribution of carbon and nitrogen. Two hours after labeling, assimilated carbon was mainly retained in the shoot (69%), whereas 7% entered the root and 24% was respired. Nitrogen, taken up via the root, was largely translocated into the shoot (85%). Salt-stressed seedlings showed decreased uptake and translocation of nitrogen (69%), whereas carbon metabolism was unaffected. Coupled to a gas chromatograph, labeling analysis provided enrichment of proteinogenic amino acids. This revealed significant protein synthesis in the panicle of adult plants, whereas protein biosynthesis in adult leaves was 8-fold lower than that in seedling shoots. Generally, amino acid enrichment was similar among biosynthetic families and allowed us to infer labeling dynamics of their precursors. On this basis, early and strong 13C enrichment of Embden-Meyerhof-Parnas pathway and pentose phosphate pathway intermediates indicated high activity of these routes. Applied to mode-of-action analysis of herbicides, the approach showed severe disturbance in the synthesis of branched-chain amino acids upon treatment with imazapyr. The established technology displays a breakthrough for quantitative high-throughput plant metabolic phenotyping.

Metabolically engineered crops are highly desired to ensure the global food supply (Khush, 2003) and to produce various chemicals and materials (Fischer and Emans, 2000; Sharma and Sharma, 2009). Without doubt, tailored plant metabolic engineering requires a good knowledge of the underlying metabolism. This explains the strong interest in tools and technologies to analyze plants on the systems level. Particularly, analysis of plant metabolic pathways and intracellular fluxes by means of isotope experiments, coupled to mass spectrometry (MS) and NMR (Ratcliffe and Shachar-Hill, 2006; Young et al., 2011), has predictive power for metabolic engineering (Kruger and Ratcliffe, 2009; Shachar-Hill, 2013). Such analyses, reported for cell suspension cultures (Rontein et al., 2002; Kruger et al., 2007; Williams et al., 2008) and isolated plant organs like leaves (Schaefer et al., 1980; Cegelski and Schaefer, 2005; Hasunuma et al., 2010), tubers (Roessner-Tunali et al., 2004), and seeds (Schwender et al., 2003; Junker et al., 2007), provide valuable insight into metabolism but fail to describe the behavior of intact, whole plants (Allen et al., 2009), which is necessary to give a systemic picture of metabolic functions under physiologically relevant conditions (Cliquet et al., 1990; Römisch-Margl et al., 2007). This is overcome by performing isotope-labeling experiments in entire plants, preferably using 13CO2, a far safer tracer compound than its radiolabeled equivalent 14CO2 (Römisch-Margl et al., 2007), combined with labeling analysis by MS and NMR (Chen et al., 2011). Such experiments, however, suffer from extended labeling time periods up to several hours or even days (Hutchinson et al., 1976; Nouchi et al., 1995; Wu et al., 2009) and CO2 concentrations beyond natural abundance to reach detectable amounts of enrichment (Römisch-Margl et al., 2007). As an example, the application of elevated CO2 levels can induce changes in plant metabolism (e.g. sink-source ratios, photosynthetic activity, and respiration), thereby affecting carbon sequestration and growth (Arp, 1991; Zhu et al., 2014). Compared with conventional MS (0.05 atom %) and NMR, combustion-isotope ratio mass spectrometry (C-IRMS) provides a far higher precision (0.0002 atom %; Meier-Augenstein, 1999b), which makes this technique particularly attractive to analyze plants at low enrichment. The high precision of C-IRMS even allows for metabolic studies without preceding tracer application (Tcherkez et al., 2003; Yousfi et al., 2012, 2013). Selected applications, which coupled C-IRMS with elemental analysis (EA), have been used to trace turnover and incorporation processes in plants (Cliquet et al., 1990; Dyckmans et al., 2000; Nogués et al., 2004) as well as to analyze plant interactions with the soil microbial community (Griffiths et al., 2004; Leake et al., 2006; Wu et al., 2009). With the availability of gas chromatography (GC)-coupled C-IRMS, enrichment analysis could be targeted to individual metabolic compounds, like sugars, fatty acids, and amino acids (Derrien et al., 2004; Olsson et al., 2005; Molero et al., 2011; Lattanzi et al., 2012).

Here, we describe a novel approach, which combines 13C- and 15N-based whole-plant studies with subsequent labeling analysis of entire plants, plant tissues, and individual metabolites using EA-C-IRMS and GC-C-IRMS for in vivo metabolic fingerprinting of the model crop rice (Oryza sativa) under physiologically relevant conditions. For the isotope experiments, specific labeling reactors were designed and constructed, which allowed precise 13C-pulse labeling of plants as well as simultaneous 13C and 15N tracing under well-defined environmental conditions. This offered a major benefit compared with previous studies: the applicability of physiological concentrations of 13CO2 and short labeling periods under highly controlled conditions regarding light, temperature, and humidity. The developed approach was applied to compare rice plants at different developmental stages, concerning assimilation, translocation, and incorporation of label into metabolic intermediates after single or double labeling with 13CO2 and 15NH4NO3. Particularly, studies combining 13C and 15N label detection in plants are rare so far (Cliquet et al., 1990; Dyckmans et al., 2000). Thereby, the interaction of carbon/nitrogen metabolism and relevant sink-source relations of individual plant organs were studied. Furthermore, a stress-induced phenotype was investigated by exposing rice seedlings to high salinity, a major abiotic stress. The examination of the mode of action of herbicide treatment further underlined the high potential of the technique to reliably quantify metabolic variation. The developed technology provides plant metabolic engineers with a sophisticated tool for fast screening and metabolic profiling of distinct phenotypes, which perfectly complements more demanding isotopically nonstationary metabolic flux analysis (Szecowka et al., 2013; Ma et al., 2014) to get a comprehensive picture of plant metabolic functions.

RESULTS

Construction of Labeling Reactors and Experimental Design

Three sizes and types of labeling reactor were designed, constructed, and validated to evaluate their suitability for in vivo 13C labeling studies (Fig. 1): two tube reactors for 13CO2 studies with soil-grown adult plants (250 L) and seedlings (100 L), respectively, and a box reactor for combined 13CO2 and 15NH4NO3 labeling studies with hydroponic seedlings (125 L). For all reactors, the wall material used allowed full transmission of light (Supplemental Fig. S1), and temperature and humidity could be maintained at desired values (Supplemental Fig. S2). Hence, the reactors allowed plants to be labeled under the same light, temperature, and humidity regimen that they were exposed to during growth in a research plant growth cabinet (phyto chamber). Immediate replacement of ambient CO2 by an equimolar level of 13CO2 was realized by an absorber unit connected to the reactor. A first set of experiments with soil-grown rice seedlings was conducted to identify the optimum conditions regarding the supply of tracer (400 or 700 µL L−1 13CO2) and the time period of incubation with 13CO2 (10, 60, and 180 min; Supplemental Fig. S3). Short incubation times of 10 min at ambient levels of 13CO2 (400 µL L−1) were sufficient to allow precise estimation of the assimilated carbon, due to the high precision of the EA-C-IRMS measurement (Supplemental Fig. S3A). Labeled under these conditions, the shoots of rice seedlings showed marked 13C enrichment (i.e. a δ value of 170‰ ± 6‰). The low deviation underlines that the assimilation was quantified with excellent reproducibility, particularly considering the high complexity of the studied plant system. Enrichment values were in an equal range after simultaneous labeling of one, three, six, or 12 plants in the same reactor for 60 min, indicating that even larger sets of plants and longer incubation times did not result in CO2 limitation (Supplemental Fig. S3B). In order to examine diurnal effects on photosynthesis and CO2 assimilation, isotopic labeling studies with seedlings were conducted every 1 h in the time frame of 2.5 to 9.5 h after sunrise. Labeling of plants at different times did not reveal significant differences from plants labeled at midday (6.5 h after sunrise; Supplemental Fig. S3C). Accordingly, the routine work flow was as follows. Rice plants were grown in a phyto chamber under ambient air, until they were placed inside the enclosure shortly before the labeling experiment. Ambient CO2 was then removed from the reactor within 30 s and replaced by an equimolar amount of 13CO2 (400 µL L−1). After 10 min of incubation in this atmosphere, plants were removed from the reactor and either harvested directly for assessment of carbon assimilation or cultivated further in the phyto chamber for assessment of carbon translocation. For simultaneous tracing of 15N, roots of hydroponically grown seedlings were supplied with 15NH4NO3. The isotopic enrichment of harvested plant material and extracted amino acids was determined using EA-C-IRMS and GC-C-IRMS, respectively.

Figure 1.
Figure 1.

Equipment designed and constructed for in vivo 13C and 15N labeling studies. A, Large tube reactor (0.5 m diameter, 1.3 m height, and 255 L volume) for 13CO2 labeling of soil-grown adult rice plants. B, Small tube reactor (0.5 m diameter, 0.5 m height, and 98 L volume) for 13CO2 labeling of soil-grown rice seedlings. C, Box reactor (0.5 × 0.5 × 0.5 m, 125 L volume) for simultaneous 13CO2 and 15NH4NO3 labeling of hydroponic rice seedlings. All reactors were equipped with a temperature control, comprising a water-cooled ventilator at the bottom plate of the reactor and an external cryostat. In addition, an external CO2 adsorption unit consisted of a high-power pump, an adsorber, and a fine dust filter. Prior to the experiments, the chosen plants were placed into the reactor, which were then closed gas tight by a rubber seal. Ambient CO2 was removed from the reactor within 30 s. The experiments were started by injecting the desired amounts of 13CO2 through an injection valve in the lid of each reactor.

Combined Assessment of Carbon and Nitrogen Metabolism in Rice Seedlings

The developed approach was next used for combined 13CO2 and 15NH4NO3 labeling of hydroponically grown rice seedlings, in order to obtain an integrated picture of carbon and nitrogen metabolism (Fig. 2). Isotopically labeled 15NH4NO3 was provided to the roots, while at the same time, 13CO2 was supplied to the shoot of a rice seedling, using the designed box reactor (Fig. 1C). Immediately after the pulse, maximum 13C enrichment was detected in the shoot (450‰ ± 45‰; Fig. 2A), while 15N labeling was highest for the root (4,130‰ ± 25‰; Fig. 2C). However, the transport of carbon and nitrogen seemed fast, because significant 15N enrichment at this time point was already found in the shoot (190‰ ± 25‰; Fig. 2D). Likewise, the root contained slight amounts of 13C (15‰ ± 5‰; Fig. 2B). Within 2 h after assimilation, 15N and 13C levels were evenly equilibrated. During the ongoing chase period, 13C and 15N enrichments decreased continuously in root and shoot. By integration of the measured 13C and 15N enrichment data, it was now possible to determine the percentage reallocation of label within 2 h after the labeling pulse (Fig. 3), thereby providing fast and quantitative access to relative carbon and nitrogen fluxes in rice plants. The root-to-shoot ratio, calculated from the labeling data via Equation 4 (see “Materials and Methods”), was 0.173. This seemed a proper estimate according to previously reported values for rice between 0.05 and 0.3 (Yoshida, 1981). The majority of assimilated nitrogen (85%) was transported to the shoot (Fig. 3A), whereas only 15% remained in the roots. Regarding assimilated carbon, the major fraction (69%) was retained in the shoot, whereas only 7% was translocated into the roots. A total of 76% of assimilated carbon was thus recovered inside the plant 2 h after assimilation, which indicated a loss of 24% via respiration. The retainment of carbon in the shoot was slightly higher than that for maize (Zea mays) plants, in which 53% of 13C is recovered inside the shoot at elongation (Meng et al., 2013). The same calculation, using labeling data from samples taken 24 h after the pulse (i.e. including a dark period), revealed an increased loss of carbon through respiration by 52% (data not shown), which agreed well with the corresponding data obtained from the measurement of dry matter production, photosynthesis, and respiration (Tanaka and Yamaguchi, 1968).

Figure 2.
Figure 2.

Impact of salt stress on carbon and nitrogen assimilation and translocation of hydroponically grown rice seedlings. The data reflect 13C (A) and 15N (B) enrichment in the shoot and 13C (C) and 15N (D) enrichment in the root. The data shown are means ± sd (n = 3) for stressed seedlings (100 mm NaCl for 6 d; white bars) and untreated controls (gray bars). At the age of 12 d, rice seedlings were simultaneously labeled with 13CO2 (400 µL L−1) through the reactor gas phase and with 15NH4NO3 (1.43 mm) supplied via the hydroponic growth medium. The labeling pulses were applied for 10 min, after which plants were either harvested directly to assess assimilation or cultivated further at ambient air and in nonlabeled medium up to 48 h to trace label translocation. The 13C and 15N enrichment of freeze-dried plant material was analyzed by C-IRMS coupled to EA. Asterisks indicate significant differences between mean values (P ≤ 0.05, Student’s t test). n.s., Not significant. The full data set is given in Supplemental Table S1.

Figure 3.
Figure 3.

Relative fluxes of assimilated carbon and nitrogen in hydroponically grown rice seedlings under control conditions (A) and exposed to salt stress (100 mm NaCl for 6 d; B), calculated from 13C and 15N enrichment data obtained 2 h after the labeling pulse (Fig. 2). The root-to-shoot ratio for seedlings under control conditions (0.173) and seedlings exposed to high salinity (0.165) was calculated from the 15N label distribution using Equations 4 and 6. Based on this ratio, the relative reallocation of label between shoot and root was determined. The total amount of assimilated carbon and nitrogen at time zero was set to 100% carbon and nitrogen uptake, respectively, in order to provide relative data. The seedlings were analyzed at the age of 12 d. The full data sets are given in Supplemental Table S1.

Impact of Salt Stress on the Assimilation and Translocation of Carbon and Nitrogen in Rice Seedlings

Hydroponically grown rice seedlings were exposed to 100 mm sodium chloride for 6 d prior to the labeling experiment. Untreated plants served as a control. Immediately after the labeling pulse, root 15N enrichment was 4,190‰ ± 25‰ in the control plant and only 2,490‰ ± 160‰ in the stressed plant, corresponding to a decreased ammonium uptake of 40% (Fig. 2). In addition, the translocation of nitrogen from root to shoot was strongly impaired, leading to significantly less enrichment (43%–62%) in the shoot of stressed plants compared with control plants at all sampling time points. In contrast, carbon assimilation in the shoot was rather unaltered (Fig. 2A). As described above for untreated control plants, the distribution of carbon and nitrogen was inferred for a stressed plant by integrating 13C and 15N labeling data. The root-to-shoot ratio estimated via Equation 4 was only slightly increased under stress conditions (0.165 ± 0.01 for control plants compared with 0.173 ± 0.03 for stressed plants). Relative carbon distribution did not change in plants exposed to stress (Fig. 3). Nitrogen distribution, however, changed significantly, leading to the recovery of 30% of the assimilated nitrogen in roots compared with 15% in control plants. The amount of labeled nitrogen transported to the shoot was decreased accordingly, resulting in 69% compared with 86% in control plants (Fig. 3B).

Quantitative Assessment of Carbon Assimilation in Adult Rice Plants

In the flowering and grain-filling stages, rice plants exhibit different leaf types (i.e. normal leaves and flag leaves). The flag leaf is the uppermost leaf on a culm and the main carbon provider of the panicle when fully developed (Rawson and Hofstra, 1969). Assimilation patterns of plants in different developmental stages, sampled immediately after a 10-min labeling pulse, were compared (Fig. 4). Most of the label was found in the leaves. Plants in the flowering stage showed similar 13C enrichment in normal leaves (260‰ ± 40‰) and flag leaves (240‰ ± 50‰; Fig. 4B). This was also observed for the early grain-filling stage. During late grain filling, however, the flag leaf was more important for the assimilation of 13CO2, indicated by significantly higher enrichment (170‰ ± 10‰ in normal leaves compared with 270‰ ± 30‰ in flag leaves), which is similar to previous findings for wheat (Triticum aestivum; Rawson and Hofstra, 1969) and consistent with its function as a major source organ for carbon transport into the panicle. The stem did not exhibit any enrichment, while the panicle showed low 13C accumulation during early grain filling (10‰ ± 5‰; Fig. 4B).

Figure 4.
Figure 4.

Carbon assimilation and translocation in adult rice plants, assessed by 13CO2 isotope experiments and labeling analysis by C-IRMS coupled to EA. A, Morphology of the studied plants with sampled leaf, flag leaf, stem, and panicle. B, Tissue-specific 13C assimilation of rice at flowering stage (68 d), at early grain-filling stage (75 d), and at late grain-filling stage (88 d), for which soil-grown plants were labeled with 400 µL L−1 13CO2 for 10 min and harvested directly for assessment of 13C enrichment. C, Morphology of the studied plants with identified carbon assimilation routes. D, Time-resolved carbon assimilation and translocation of rice plants at late grain-filling stage (88 d), for which soil-grown plants were labeled with 400 µL L−1 13CO2 for 10 min and harvested directly or further cultivated at ambient air for 2, 4, 24, and 48 h prior to harvesting. In all cases, 13C enrichment of freeze-dried plant material is displayed as δ13C (‰), corrected for natural labeling. Mean values ± sd (n = 3) are shown. Different letters (a, b, or c) indicate significant differences between means (P ≤ 0.05, one-way ANOVA with Tukey’s test) of sampled organs at the individual time points. The full data sets of these experiments are given in Supplemental Tables S2 and S3.

Quantitative Assessment of Carbon Translocation in Adult Rice Plants

In order to assess carbon translocation, plants were postcultivated in the phyto chamber after a labeling period of 10 min. Samples taken after distinct chase periods provided a time-resolved 13C sequestration pattern. Immediately after the 13CO2 pulse, most of the label was recovered in the leaves (Fig. 4D). Within 2 h of further growth, the 13C enrichment of flag leaves and normal leaves declined by 45% and 41%, respectively, while the enrichment in the stem and panicle increased. This trend continued until a maximal enrichment was reached after 24 h for the panicle (100‰ ± 20‰) and after 48 h for the stem (50‰ ± 15‰; Fig. 4D). As for the seedling experiments, the data for the adult plants showed high precision and reproducibility.

Quantification of 13C and 15N Amino Acid Enrichment Using GC-C-IRMS

Using GC-C-IRMS, the measurement of labeling enrichment was extended to amino acids. For each amino acid eluting from the GC column, the 13C and 15N enrichment was given by the ion intensity at a mass-to-charge ratio (m/z) of 45 and 29, reflecting 13CO2 and 14N15N, respectively, formed by combustion in the instrument. For 16 amino acids, satisfying signal quality was generally obtained and provided precise estimates of their labeling status. Hereby, the amino acid pairs Glu/Gln and Asp/Asn were each quantified as lumped pools, due to conversion of the carboxamides Asn and Gln into their corresponding acids during the protein hydrolysis step of sample processing (Wittmann, 2007). Four amino acids (Cys, Met, Trp, and Arg) were not accessible because they were degraded during this treatment (Wittmann, 2007). Generally, 5 mg of lyophilized material was sufficient to provide high-quality data, independent of the type of tissue processed. The conditions used for extraction, precipitation, and derivatization of protein from lyophilized plant material was crucial with regard to the yield and purity of the amino acids obtained. In contrast to extraction in Tris buffer (pH 8.8), extraction in hot water (100°C, 15 min) yielded much less protein (data not shown). Similarly, precipitation of the extracted protein in ice-cold 10% (w/v) TCA was less efficient than precipitation in ice-cold acetone (data not shown). Additional tests with alternative derivatization agents revealed that trimethylsilyl derivatives of the amino acids (e.g. obtained with trimethylsilyl-trifluoroacetamide) were not fully separated by GC. Even a set of variations in the temperature profile did not allow full baseline separation for the amino acids Met/Asp, Ile/Pro, and Glu/Phe. Full baseline separation was necessary, however, as the combustion of analytes into CO2 and N2 prior to detection does not allow one to discriminate between overlapping analyte peaks. Derivatization with methyl-t-butyldimethylsilyl-trifluoroacetamide into t-butyldimethylsilyl derivatives finally led to full baseline separation of the target analytes. Some of the seedling samples, however, did not provide an unambiguous signal for Tyr, probably due to matrix overlay. Due to the fact that interference with background noise or matrix effects leads to false results in isotope experiments (Wittmann, 2007), this amino acid was partly excluded from further interpretation. It also turned out that the addition of dimethylformamide, commonly used to process microbial samples (Wittmann, 2007), was not compatible with the GC-C-IRMS instrument used, because the solvent was largely transferred into the combustion chamber. Accordingly, derivatization was conducted without the addition of solvents. Tests with different incubation times (30, 60, 90, and 120 min) and temperatures (80°C, 90°C, and 100°C) revealed that the combination of 60 min and 80°C provided the optimum signal-to-noise ratio.

Isotope Distribution Patterns

Dynamic Incorporation of Carbon into Protein Amino Acids

The developed protocol was now used to quantify 13C distribution patterns in rice related to amino acid metabolism (Fig. 5). A first study with seedlings revealed that enrichment increased with time, as 13C was incorporated continuously into cell protein. Amino acids differed strongly with regard to label incorporation, which seemed to correlate to their biosynthetic origin. Particularly, Tyr and Phe, stemming from intermediates of the Embden-Meyerhof-Parnas (EMP) pathway (phosphoenolpyruvate) and of the nonoxidative pentose phosphate (PP) pathway (erythrose 4-phosphate), were enriched rather fast and to a greater extent than all other amino acids and contributed up to 9% and 15% of the entire enrichment, respectively (Fig. 5A). Immediately after the pulse, significant 13C incorporation also was observed for amino acids stemming from pyruvate, another intermediate of the EMP pathway (i.e. Ala, Ser, Gly, Val, and Leu). In contrast, labeling enrichment was delayed for amino acids synthesized from 2-oxoglutarate and oxaloacetate, intermediates of the tricarboxylic acid cycle (Fig. 5A). Generally, highest enrichments were detected 24 h after the labeling pulse. After 48 h, the enrichment declined for most amino acids, probably due to a dilution with 12CO2 taken up during the postlabeling incubation. The 13C labeling profiles of Gly and Ser were similar, indicating that they originate from the same metabolic precursor, 3-phosphoglycerate (Wittmann, 2007). The same trend also was found for other amino acid families, like the Asp family of amino acids, with Thr, Lys, Ile, and Asp itself. In comparison with rice seedlings, the general amino acid enrichment was, on average, 8 times lower in the leaf of an adult plant during the late grain-filling stage (Fig. 5A). This was interesting because the total assimilation of carbon of both tissue types was in the same range (Fig. 4B; Supplemental Fig. S3) and matches perfectly with the changing role of leaves from a strong sink during development to a major source during reproduction, assimilating but not incorporating carbon dioxide (Thrower, 1962; Turgeon, 1989). Low enrichment was equally observed for normal leaves (60‰ ± 10‰ total amino acid enrichment), flag leaves (70‰ ± 10‰ total amino acid enrichment), and stem (40‰ ± 25‰ total amino acid enrichment) within 1 d of label translocation (Fig. 5B). In contrast, the panicle of adult rice plants was much more active regarding amino acid metabolic pathways (280‰ ± 30‰ total amino acid enrichment). Here, highest enrichment was detected for Phe (39‰ ± 3‰) and Tyr (30‰ ± 2‰), followed by Ala (28‰ ± 4‰), Glu (23‰ ± 2‰), and Leu (22‰ ± 3‰), which was in accordance with the pattern detected for rice seedlings. The other amino acids showed lower enrichment (Fig. 5B).

Figure 5.
Figure 5.

Incorporation of 13C into protein amino acids upon 13CO2 labeling. Enrichment of extracted amino acids was analyzed by GC-C-IRMS. A, Time-resolved pattern of a rice seedling (top, age of 12 d) and an adult rice plant at late grain filling (bottom, age of 88 d), for which soil-grown plants were labeled with 400 µL L−1 13CO2 for 10 min and then harvested directly or further cultivated at ambient air for 2, 4, 24, and 48 h prior to harvesting. Statistical analysis was conducted using Student’s t test, whereby significant differences (P ≤ 0.05) between seedling and adult leaves are marked with asterisks. B, Tissue-resolved pattern of an adult rice plant at late grain filling, for which plants were labeled with 400 µL L−1 13CO2 for 10 min followed by 24 h of cultivation at ambient air prior to harvesting of leaf, flag leaf, stem, and panicle. Statistical analysis was done by one-way ANOVA with Tukey’s test, whereby different letters (a, b, or c) indicate significant differences between means of the different tissues. C, Tissue-specific amino acid metabolism, visualized as Venn diagrams, which display the relation of amino acids based on the statistical significance between measured 13C enrichments. Significant differences between means of amino acid 13C enrichments (P ≤ 0.05) were determined by one-way ANOVA with Tukey’s test. Amino acids that do not show significantly different 13C enrichment are located in equally colored ellipses. The enrichment data are provided as mean values (n = 3) and reflect atomic percent excess corrected for natural isotopes. The full data sets are given in S4 to S6, respectively. To facilitate comparison, the data are normalized for the highest enrichment of each data set, which was set to 100%, and visualized by a color code between yellow (0%) and red (100%). CIT, Citrate; E4P, erythrose 4-phosphate; F6P, Fru-6-P; FUM, fumarate; GAP, glyceraldehyde 3-phosphate; G6P, Glc-6-P; MAL, malate; OAA, oxaloacetate; 2OG, 2-oxoglutarate; PEP, phosphoenolpyruvate; 3PG, 3-phosphoglycerate; PYR, pyruvate; R5P, ribose 5-phosphate; RU5P, ribulose 1,5-bisphosphate; SDL, seedling shoot; SUC, succinate.

Combined 13C and 15N Incorporation into Protein Amino Acids

Amino acids of the shoot were analyzed for their 13C and 15N enrichment from combined 13CO2 and 15NH4NO3 labeling experiments with hydroponically grown rice seedlings (Fig. 6). For six selected amino acids (i.e. Ala, Gly, Pro, Ser, Asp, and Glu), root-based data with satisfying quality could be derived, which allowed a tissue-specific examination, at least for these molecules (Fig. 6). Immediately after labeling, strong 15N enrichment was detected for Ser, Asp, and Glu of root protein. At the same time, Ala, Gly, and Ser, extracted from shoot protein, revealed significant 13C enrichment (Fig. 6). Within 2 h, labeled compounds were distributed inside the plant, leading to combined 13C- and 15N-enriched amino acids in shoot and root. Although all amino acids exhibited significantly different 13C and 15N enrichment, the strongest differences were found for shoot amino acids. Ala and Ser exhibited higher 13C enrichment, whereas Pro, Asp, and Glu were more strongly enriched with 15N. Four hours after the labeling pulse, similar amino acid enrichment patterns of shoot and root indicated the equilibration of label between these organs (Fig. 6). Amino acid enrichment patterns were similar for soil-grown and hydroponically grown rice seedlings (Supplemental Fig. S4), indicating that hydroponic cultivation did not significantly influence at least this part of metabolism.

Figure 6.
Figure 6.

Integrated analysis of carbon and nitrogen metabolism by combined labeling of hydroponically grown rice seedlings with 13CO2 and 15NH4NO3. Tissue-specific enrichment of extracted amino acids was quantified by GC-C-IRMS. Integrated views on transport and biosynthetic routes of Ala, Gly, Ser, Glu/Gln, Asp/Asn, and Pro regarding assimilated 13C (light gray) and 15N (dark gray) labeling (A), assessed in shoot (B) and root (C), are represented by bar graphs over the first 4 h of tracing. The data reflect means ± sd (n = 3). At the age of 12 d, rice seedlings were simultaneously labeled with 400 µL L−1 13CO2 and 1.43 mm 15NH4NO3 for 10 min and then either harvested directly for assessment of label assimilation or cultivated further at ambient air for 2 to 4 h for assessment of label translocation. Asterisks indicate significant differences between mean values at P ≤ 0.05 (Student’s t test). APE, Atomic percent excess; n.s., not significant. The full data set is given in Supplemental Table S7.

Mode-of-Action Analysis: Effect of Imazapyr Treatment on Rice Seedlings

Herbicide treatment was used as a proof of concept to demonstrate the potential of the established technology for mode-of-action studies. Imazapyr was chosen as a widely used herbicide, with a well-described mechanism of action (i.e. the inhibition of acetolactate synthase in branched-chain amino acid biosynthesis). The studies were conducted using 12-d-old, soil-grown rice plants, which were exposed to imazapyr treatment or to a control treatment. Plants were pulse labeled with 13CO2 4 h after herbicide application (Fig. 7). At the time point of the labeling experiment, no phenotypic alterations of plant morphology, as compared with the control plants, were observed (data not shown). The overall carbon assimilation at this time point was not disturbed, as indicated by equal 13C shoot enrichment of stressed and control plants, namely 586‰ ± 26‰ and 595‰ ± 16‰, respectively (Fig. 7A). However, strongly diminished label incorporation was detected in proteinogenic amino acids, which was particularly pronounced for the branched-chain amino acids 2 h after the labeling pulse (Fig. 7B). Amino acid enrichment of stressed plants reached 19% to 75% of the enrichment detected in control plants, except for the branched-chain amino acids, which only reached 4% to 11%. On average, the enrichments were 2.7 times lower in imazapyr-treated plants than in control plants, with the exception of branched-chain amino acids, which exhibited 7 to 26 times less 13C enrichment. Observable phenotypic effects became evident 7 d after imazapyr application and comprised inhibition of growth, chlorosis of aboveground plant parts, as well as a dieback of young leaves (Fig. 7C).

Figure 7.
Figure 7.

A and B, Mode-of-action analysis of the effect of the herbicide imazapyr on rice seedlings using 13CO2 labeling in combination with EA-C-IRMS to assess carbon assimilation (A) and with GC-C-IRMS to assess 13C enrichment of extracted proteinogenic amino acids (B). The experimental setup contained seedlings at the age of 12 d subjected to imazapyr (62.5 g ha−1 active ingredient) or control treatment (62.5 g ha−1 control solution). Four hours after the treatment, seedlings were labeled for 10 min with 400 µL L−1 13CO2. The assimilation of 13C, determined immediately after the labeling pulse from freeze-dried plant material, is expressed as δ13C (‰), corrected for natural isotopes. The enrichment of extracted amino acids was determined after 2 h of further cultivation at ambient air. The δ13C values of the amino acids of imazapyr-treated rice seedlings were normalized to those of the control seedlings. C, Phenotypes of rice seedlings 7 d after treatment with the control solution (left plant) and the imazapyr solution (right plant). Asterisks indicate significant differences between mean values of imazapyr-treated and control plants at P ≤ 0.05 (Student’s t test). n.s., Not significant. Mean values ± sd (n = 3) are shown. The full data sets are given in Supplemental Tables S8 and S9.

DISCUSSION

The quantitative analysis of pathway function and regulation is key to understanding and engineering plant physiology (Maliga and Graham, 2004). Here, we developed a cost-effective, high-throughput approach to assess whole-plant metabolic phenotypes in vivo. As shown, we coupled 13CO2 and 15NH4NO3 pulse studies under precisely controlled physiological conditions with ultra-precision GC-C-IRMS for parallel 13C and 15N labeling analysis in different plant tissues and even individual molecular compounds to elucidate plant metabolic traits. Different tube reactor layouts enabled 13CO2 isotope experiments with soil-grown seedlings and adult plants, up to a height of about 1 m (Fig. 1, A and B), whereas parallel 13CO2 and 15NH4NO3 labeling with hydroponic plant cultures could be conducted in a specific box reactor (Fig. 1C). In contrast to previous techniques (Tanaka and Osaki, 1983; Nouchi et al., 1995; Römisch-Margl et al., 2007), our methodology minimizes potential alterations of the studied plant during the experiment due to an atmosphere with ambient CO2 levels, controlled temperature, humidity, and illumination, and incubation times of only 10 min. The careful experimental layout provided data with high precision and reproducibility among replicates, independent of the developmental stage of the analyzed plants. Assimilation and translocation of carbon in different tissues (Figs. 3 and 4) and even individual molecules (Fig. 5) could be quantified at deviations below 20% for adult plants. Given the fact that plants in advanced developmental stages are rather complex and subject to a certain biological variation, due to differentiation into specific organs and cell types, the precision and reproducibility can be regarded as excellent. For seedlings, they were partially even higher (Figs. 6 and 7). This allowed us to accurately discriminate metabolic properties differing only slightly, which seems a valuable characteristic of our approach.

Assessment of Important Characteristics of Carbon Metabolism

Beyond technical precision and accuracy, it was further important to validate the extent to which the method could assess key properties of plant physiology. A catalog of experiments addressed this issue. Grain yield, the most prominent characteristic of crop plants, is strongly dependent on the source-sink relationship between plant parts (Kato et al., 2004), whereby the operational mode of a distinct plant organ, as source or sink, changes throughout development (Meng et al., 2013). Pioneering studies with rice plants, using radioactive 14CO2 at high dosage, had revealed the translocation of assimilated carbon into the panicle during grain filling (Cock and Yoshida, 1972). This was quantitatively assessed here, however, by much safer and easier handling using stable 13CO2. Most of the assimilated carbon was recovered inside the rice panicle 24 h after the pulse (Figs. 4D and 5B). In line with this, a 90% decrease of 13C in the assimilating tissue of plants from the late grain-filling stage was detected during this chase period (Fig. 4D), which is in the range of values reported for other plants (Leake et al., 2006). During development from flowering to late grain filling, the relative contribution of different leaves to carbon assimilation probably corresponds to changing metabolic requirements (Meng et al., 2013). During late grain filling, the lower activity of carbon assimilation in mature leaves, relative to the flag leaf, indicated mechanisms of senescence (Fig. 4). In senescing leaves, the Rubisco content and, as a consequence thereof, the photosynthetic activity decrease rapidly. Therefore, mature leaves cannot assimilate as much CO2 as younger leaves (Makino et al., 1984). At night, 13C was further lost by respiration. Additional carbon loss might have resulted from a combination of translocation to tissues not analyzed (e.g. the roots of plants grown on soil) and dilution of the label by overall plant biomass increase during the chase period (Leake et al., 2006).

Integrated Analysis of Carbon and Nitrogen Metabolism

The setup furthermore allowed combined labeling studies with 13CO2 and 15NH4NO3, which are interesting due to the close connection of carbon and nitrogen metabolism in plants but have been conducted only rarely (Cliquet et al., 1990; Dyckmans et al., 2000). The studies highlighted fast interorgan distribution of carbon and nitrogen in seedlings within 2 h after assimilation (Fig. 2), whereby the shoot operated as a major sink and exhibited a 10- and 6-fold higher demand for carbon and nitrogen compounds, respectively, compared with the root (Fig. 3A), which reflects sufficient supply with water and nutrients, especially nitrogen (Wilson, 1988; Peuke et al., 1994). Obviously, the examined seedlings received all essential macronutrients and micronutrients and were exposed to optimal breeding conditions, concerning light, temperature, and humidity, so that carbon and nitrogen were used mainly for shoot growth and development. The relative flux maps for carbon and nitrogen, giving the relative distribution among the different tissues on the basis of isotope enrichment data, provide a straightforward snapshot of plant metabolism (Fig. 3). Given the available instrumentation, such insights can be easily provided within 1 d after an isotope experiment and thus allow for a fast evaluation (e.g. to study environmental stresses as demonstrated for salt-stressed rice; Figs. 2 and 3B). In light of breeding stress-tolerant plant lines, an important area of application is metabolic phenotyping in order to identify protective mechanisms (Cramer et al., 2011) and changes in sink-source relations (Roitsch, 1999; Albacete et al., 2014). Our data reflect these features for plants treated with salt, a major abiotic factor, particularly affecting the growth and productivity of salt-sensitive crops (Roy et al., 2014). Salt stress resulted in a strong perturbation of nitrogen uptake by the root and transport to the shoot, whereas carbon assimilation and translocation were not significantly affected. Stressed plants kept relatively more nitrogen in the root as compared with nonstressed plants (Fig. 3), probably to support the supply with nitrogen-containing compatible solutes (Wang et al., 2012). Furthermore, enhanced retention of nitrogen compounds in the root might be due to adaptive mechanisms to ensure adequate water and nutrient acquisition from the rhizosphere (Sharp et al., 2004).

Labeling Dynamics of Amino Acids Provide Qualitative Insight into Metabolic Pathways

The coupling of C-IRMS with GC separation, together with the development of suitable protocols for sampling and sample processing, provided time-resolved enrichment data for protein-derived amino acids across different tissues of rice. Amino acids are the analytes of choice for microbial pathway analysis, because they are much more abundant in cell extracts and protein than their precursors and provide extensive labeling information (Wittmann, 2007). On basis of the underlying biosynthetic precursor amino acid relationship, it is easy to deduce the labeling patterns of the precursor metabolites from labeling patterns of the corresponding amino acids. The 13C labeling of amino acids from the same biosynthetic family was similar and obviously reflected the enrichment of their common precursor (Fig. 5A). In the seedling, amino acids stemming from precursors of the EMP pathway and the nonoxidative PP pathway exhibited fast and strong 13C enrichment (Fig. 5A, top), examples being Phe, Tyr, Ser, Gly, and His. In contrast, Glu, Pro, Asp, and Thr, originating from tricarboxylic acid cycle-based precursors, were labeled much slower and weaker. Although this does not directly provide quantitative flux rates, the 13C enrichment data reveal a fast and strong influx of 13C into the EMP pathway and the nonoxidative PP pathway, indicating high activities of these routes. The rather low enrichment of tricarboxylic acid cycle-related amino acids most likely reflects a down-regulation of the cycle in the light (Tcherkez et al., 2005). In addition, the slow dynamics could be an indication that Glu, Asp, and amino acids derived from them are not formed in the shoot but rather are synthesized in the root, followed by transport into the shoot. This is indeed taking place, which is discussed below on the basis of integrated 13C and 15N labeling data (Fig. 6). The 13C enrichment in the shoot of a seedling was about 8- to 10-fold higher than that in the leaf of an adult rice plant (Fig. 5A, bottom). Adult leaves assimilated the provided 13CO2 to a high extent (Fig. 4) but incorporated only little of it into protein. This matches with the changing role of leaves from sink to source during reproduction, assimilating but not incorporating carbon dioxide (Thrower, 1962; Turgeon, 1989).

Labeling Dynamics of Amino Acids Indicate Tissue-Specific Metabolism

The 13C labeling of amino acids differed largely between individual tissues. For rice at late grain filling, leaf, flag leaf, and stem incorporated only little carbon into protein (Fig. 5B). The panicle showed the highest 13C enrichment among all tissues. Most assimilated carbon was hence translocated into the panicle, where it was incorporated into proteinogenic amino acids. The panicle exhibited an active de novo protein biosynthesis, reflecting that filling of the grains results in a strong demand for protein precursors (Cock and Yoshida, 1972). A compound-oriented view, based on the statistical significance of labeling patterns, groups amino acids into colored ellipses according to their labeling similarity (Fig. 5C). This immediately highlights specific metabolic fingerprints for all tissues of rice. Leaf and flag leaf differed only in a few amino acids, whereas stem and panicle revealed drastically altered patterns and evidence for a tissue-specific carbon metabolism. This type of visualization further highlighted strong differences between the carbon metabolism of an adult leaf and a young shoot.

Labeling Dynamics Provide Spatial Resolution of Amino Acid Metabolism

Combined 13C and 15N labeling of hydroponic rice seedlings showed an immediate occurrence of 15N-labeled Glu/Gln and Asp/Asn in the root, whereas the 13C-labeled forms appeared much later (Fig. 6C). Obviously, these amino acids were formed from carbon precursors in the root through 15NH4 assimilation and transamination (Lam et al., 1995), which explains the exclusive enrichment with 15N (Fig. 6, A and C). Subsequently, they were transported into the shoot (Funayama et al., 2013) to serve as amino group donors for the biosynthesis of other amino acids (Kiyomiya et al., 2001). Glu, with its rather high 15N and low 13C enrichment, synthesized in the root and transported to the shoot (Fig. 6B, 2-h time point), is the precursor for the de novo synthesis of Pro, exhibiting a similar labeling pattern.

The immediate 13C enrichment (Fig. 6B, 0-h time point) indicates a fast biosynthesis of Ala, Gly, and Ser in the shoot. For Gly and Ser, this may be due to photorespiration, which typically leads to high turnover rates for these amino acids (Gauthier et al., 2010). Overall, this provides a spatially resolved picture of amino acid metabolism (Fig. 6), which explains the different dynamics of 13C and 15N enrichment. From similar effects after simultaneous labeling of rape (Brassica napus) plants with 13C and 15N, it has been hypothesized that the incorporation of assimilated 13C into amino acids is not tightly connected to nitrogen assimilation (Gauthier et al., 2010). This seems to also hold for rice.

The Response of Rice to the Herbicide Imazapyr Comprises Impaired Biosynthesis of Branched-Chain Amino Acids and Enhanced Protein Turnover

Upon treatment with imazapyr, the biosynthesis of Val, Leu, and Ile was strongly inhibited (Fig. 7B), observable already 6 h after treatment. The overall carbon assimilation of the treated plant, however, was unaffected (Fig. 7A). This distinct phenotype perfectly matches with the known mode of action of imazapyr. The herbicide is highly target specific. The enzyme acetohydroxyacid synthase, a key step in branched-chain amino acid biosynthesis, is the only site of action of this herbicide (Tan et al., 2005). In the longer term, imazapyr causes a dysfunction of cell growth as well as disruptions of DNA and protein biosynthesis and increased protein turnover to recycle branched-chain amino acids (Shaner and Reider, 1986; Scarponi et al., 1995; Royuela et al., 2000). As there was no more de novo synthesis, Val, Leu, and Ile exhibited lowest enrichment (3‰ ± 3‰ to 10‰ ± 3‰) among all amino acids. In addition, our analysis demonstrates that metabolic changes at this early time point were not restricted to branched-chain amino acids as primary targets. In fact, metabolism was affected much more globally. Newly assimilated 13C was incorporated into protein to a lesser extent in herbicide-treated plants than in control plants (Fig. 7B). Growth defects were evident 7 d after imazapyr application (Fig. 7C), indicating a slow rate of plant death, which is related to the amount of intracellularly stored amino acids (Shaner and Singh, 1991). In this regard, our profiling toolbox appears valuable to study the mode-of-action of synthetic compounds at the initial level of plant phenotyping, the first level of a three-tiered approach for mode-of-action identification (Tresch, 2013).

CONCLUSION

Taken together, the developed approach is suitable to conduct stable isotope-labeling experiments for in vivo whole-plant metabolic profiling. The high technical data quality achievable under physiologically relevant conditions seems particularly promising to be applied to (1) stress-response studies, (2) phenotypic screening of plant lines, (3) mode-of-action studies, and (4) integrated analysis of carbon and nitrogen metabolism, among others. The underlying tracer studies require little time and low effort compared with model-based approaches and are potent as a screening tool (Schwender, 2008). Clearly, this type of analysis does not, per se, provide quantitative intracellular fluxes through individual reactions and pathways, but it can suggest metabolic activities (i.e. reallocation profiles or metabolic fingerprints). In this regard, our approach provides a useful complementation to the more demanding approaches of isotopically nonstationary metabolic flux analysis (Szecowka et al., 2013; Ma et al., 2014). The latter offers the greatest potential for quantitative resolution of metabolic fluxes in autotrophic plants but involves extreme experimental and computational effort, high cost, and low throughput to derive flux information. In this regard, future combinations of both technologies for two-tiered complementary analysis could provide plant physiologists with a sophisticated toolbox for initial screening of several distinct phenotypes, thereby identifying the most promising ones for more comprehensive analysis. The high-precision GC-C-IRMS analysis, demonstrated here for amino acids, might be easily widened to fatty acids (Meier-Augenstein, 2002; Richter et al., 2010; Panetta and Jahren, 2011), sterols (Jones et al., 1991), monosaccharides (Docherty et al., 2001; Derrien et al., 2003), and lignin (Goñi and Eglinton, 1996), which are all accessible via such an instrumentation. This promises to extend the approach to other pathways of primary metabolism (e.g. lipid, sugar, and cell wall biosynthesis) as well as to pathways of secondary metabolism (e.g. involving phenol, isoprenoid, and alkaloid biosynthesis).

MATERIALS AND METHODS

Plants

Rice (Oryza sativa ssp. japonica ‘Nipponbare’) plants were obtained from CropDesign.

Chemicals

As a tracer, 13CO2 (greater than 99 atom % 13C) was purchased from Eurisotop. Labeled 15NH4NO3 (greater than 98 atom % 15N) was purchased from Sigma-Aldrich.

Media

Plants were grown either on soil (Einheitserde type GS90; 70% organic fiber peat and 30% clay, pH 5.5–6; Einheitserde- und Humuswerke Gebr. Patzer) or on hydroponic medium (1.43 mm 15NH4NO3, 1 mm calcium chloride hexahydrate, 0.18 mm magnesium sulfate heptahydrate, 1.32 mm potassium sulfate, 0.32 mm monosodium phosphate, 1 mm ferric ethylendiaminetetraacetic acid, 8 µm manganese [II] chloride tetrahydrate, 0.15 µm zinc sulfate heptahydrate, 0.15 µm copper [II] sulfate pentahydrate, 0.075 µm ammonium heptamolybdate, and 1.39 µm boric acid; based on Yang et al., 1994). In isotope experiments, naturally labeled NH4NO3 was replaced by an equimolar amount of 15NH4NO3.

Plant Growth Conditions

Rice seeds were germinated on moist filter paper in a petri dish for 4 d at 26°C in the dark. The seeds were transferred into light (500 µmol m−2 s−1 photosynthetically active radiation) 1 d before they were transplanted either into 0.7-dm3 pots used for further cultivation on soil or into hydroponic boxes. Prior to sowing, pots were soaked with deionized water containing 0.15% of the fungicide proplant (Stähler). Seeds were subjected to hot water treatment (60°C for 10 min) to prevent sheath rot. Rice plants were then grown under a 13/11-h day/night cycle at an average irradiance of 500 µmol m−2 s−1 photosynthetically active radiation during the light phase (Powerstar HQI-BT 400W; Osram), a temperature cycle of 26°C/21°C, and a relative humidity of 60%. During the first 14 d of development, plants were irrigated two times per day with deionized water. During the first 3 weeks, plants were watered via top irrigation and later via subirrigation. Between weeks 3 and 10, plants were fertilized with Hakaphos-Blau solution (0.3% [v/v] in deionized water; Compo) twice per week, replacing one deionized water treatment, respectively. Plants in different developmental stages were used for 13CO2 labeling experiments. Rice seedlings were generally used for experimental purposes after 12 d of cultivation. Flowering plants, as well as plants from the early and late grain-filling stages, were examined at 68, 75, and 88 d, respectively. For hydroponic cultures, plants were grown in hydroponic containers (27 × 17 × 12 cm) covered with a perforated Styrofoam plate. Plastic meshes were placed inside the holes (2 cm diameter) on which pregerminated seedlings were cultivated with their roots freely suspended in the hydroponic medium. Rice seedlings were generally used for experimental purposes after 12 d of cultivation. The hydroponic cultures were incubated under the same conditions regarding light, temperature, and humidity as soil-grown plants.

High-Salt Treatment

In salt stress experiments, hydroponically growing seedlings were subjected to high-salt treatment for 6 d. For that purpose, 100 mm NaCl was added to the growth medium.

Imazapyr Treatment

Prior to the labeling experiment, soil-grown seedlings were subjected to imazapyr treatment, a nonselective herbicide of the imidazolinone group. The imazapyr solution (0.3 mm imazapyr [BASF], 0.1% [v/v] dimethyl sulfoxide, and 0.1% [v/v] Dash E.C. [BASF]) was applied with an air brush to reflect a dosage of 62.5 g ha−1. Control plants were subjected to a solution containing only the solvents used (0.1% [v/v] dimethyl sulfoxide and 0.1% [v/v] Dash E.C.). Labeling experiments were conducted 4 h after herbicide application.

Isotopic Labeling Experiments with 13CO2

The labeling experiments were conducted in specifically constructed labeling reactors (Fig. 1). A large tube reactor (0.5 m diameter, 1.3 m height, and 255 L volume) was designed for 13CO2 isotope experiments with soil-grown adult plants (Fig. 1A), and a small tube reactor (0.5 m diameter, 0.5 m height, and 98 L volume) served for 13CO2 isotope experiments at the seedling stage (Fig. 1B). The tube reactors were built from Plexiglas acrylic sheets (5 mm thickness; Hans Keim Kunststoffe). The material allowed full spectral transmission of sunlight at wavelengths between 400 and 900 nm, containing the essential spectral interval for plant growth (Supplemental Fig. S1). Ethylene propylene diene monomer rubber (Mercateo) was used as sealing material, because of its high flexibility and endurance. The rubber sealing was agglutinated to the Plexiglas or polycarbonate sheets with solvent-free glue (Loctite 406; Henkel). The tube was conglutinated to the lid with a two-component adhesive (Pattex Stabilit; Henkel). For the maintenance of a constant temperature, a cooling system with a water-cooled ventilator (Peltier cooler/heater, 380 W, 24 V; Uwe Electronic) connected to an external cryostat (Lauda RMT20; Lauda Dr. R. Wobser) was installed. The ventilator and the connectors were attached to the bottom plate of the reactor. To keep the humidity level at or above 60% of saturation during the experiments, water-soaked cloth was placed in a glass beaker inside the enclosure. Temperature and relative humidity were monitored online by a humidity and temperature logger (Voltcraft DL-120 TH; Conrad Electronic). In addition, the CO2 concentration was measured (Voltcraft CM-100; Conrad Electronic). All reactors allowed a precise adjustment of the 13CO2 level. For this purpose, they contained two perforated pipes, one in the upper back part (exhaust air) and one in the lower back part (supply air). These were connected to a CO2 adsorption unit, consisting of a high-power pump (6,000 L min−1; Bravo 2000, 220 V; Scoprega), a fine dust filter (Filter Cartridge A; Kärcher), and a CO2 adsorber (5 L; Drägersorb 800+; Drägerwerk). All power supplies, except for the external absorber pump, had 24-V D.C. to allow safe handling. All labeling reactors were installed inside the phyto chamber (Svalöf), directly beside the benches, where rice plants were grown at ambient air prior to and after the labeling experiments. For the labeling studies, plants were placed inside the enclosure. Hereby, the soil of the plant pots was covered with plastic wrap to avoid potential interference of CO2 respired from soil with the defined gas atmosphere. The ambient CO2 was removed (less than 20 µL L−1) by adsorption for a short time period of about 30 s as described above. Immediately after purging, the desired amount of 13CO2 was injected through a valve (screw cap with silicone diaphragm), positioned in the lid of each enclosure, and the plants were then incubated for a defined labeling period. Afterward, the plants or specific parts were harvested directly or cultivated further in the phyto chamber under ambient air prior to analysis. All harvested plants or plant tissues were immediately deep frozen in liquid nitrogen to stop metabolic activity. At each sampling time point, at least three biological replicates were obtained. In the case of seedling experiments, the whole shoot was harvested. Roots were collected from hydroponically grown plantlets and treated equally. Of a full-grown plant, five tillers were harvested, whereby flag leaf, leaf, stem, and panicle were separated, followed by immediate quenching in liquid nitrogen. The individual tissues originating from the five tillers were pooled. The outermost, photosynthetically active leaves were removed from the stem prior to further treatment. Experiments were generally performed at 4 and 8 h after sunrise.

Combined 13C and 15N Labeling Experiment

A box reactor (carbon/nitrogen reactor; 0.5 × 0.5 × 0.5 m, 125 L volume) was developed for combined 13CO2 and 15NH4NO3 labeling with hydroponic rice cultures (Fig. 1C). Ammonium nitrate was selected because it generally serves as a nitrogen source and is taken up by the roots. Rice prefers ammonium over nitrate, as demonstrated by the higher uptake rate. Compared with nitrate, its uptake is less dependent on light intensity and oxygen concentration at the root site (Sasakawa and Yamamoto, 1978). The reactor was built from polycarbonate (5 mm thickness; Hans Keim Kunststoffe), which allowed full spectral transmission of sunlight (Supplemental Fig. S1). Plants were pregrown in the phyto chamber as hydroponic cultures. Prior to the experiment, cultures were transferred from naturally labeled growth medium to a container with 15NH4NO3 medium. The container was then placed inside the reactor on a perforated plate (polyvinylchloride, 5 mm; Hans Keim Kunststoffe), and the enclosure was closed tightly via fixation clamps. Immediately afterward, the 13CO2 pulse was applied, as described above. Monitoring and control of temperature, humidity, and 13CO2 level were done as described for the tube reactors (see above). At the end of the labeling incubation period, the box reactor was opened to ambient air and the plants were either harvested directly or retransferred into naturally labeled growth medium after washing of the roots with naturally labeled growth medium. Sampling and sample processing were done as described above. Experiments were generally performed at 4 and 8 h after sunrise.

Quantification of Isotopic 13C and 15N Enrichment

Briefly, deep-frozen plant material was freeze dried (Christ Gamma 2-16 LSC; Martin Christ Gefriertrocknungsanlagen) and ground to a fine powder in a ball mill (3–5 min, 30 Hz; Retsch MM300; Retsch). A sample (0.8–0.9 mg dry weight) was then transferred into a tin capsule (3.5 × 5 mm; HEKAtech). The isotopic enrichment was determined using an elemental analyzer (FLASH 2000; Thermo Scientific) coupled to an isotope-ratio mass spectrometer (Delta V Plus; Thermo Scientific). The gas flow was set to 300 mL min−1, and the column temperature was kept at 41°C.

Quantification of Isotopic 13C and 15N Enrichment of Proteinogenic Amino Acids

Deep-frozen plant material was freeze dried (Christ Gamma 2-16 LSC; Martin Christ Gefriertrocknungsanlagen) as described previously (Hurkman and Tanaka, 1986), with slight modifications as outlined below. Samples of approximately 5 mg dry weight were mixed with 400 µL of extraction buffer (0.175 m Tris-HCl, pH 8.8, 5% [w/v] SDS, 15% [v/v] glycerol, and 0.3 m dithiothreitol), followed by centrifugation (13,000g, 10 min, and room temperature). The supernatant was mixed with 1.6 mL of ice-cold acetone and incubated for precipitation of cell protein for 1 h at −20°C. After centrifugation (13,000g, 10 min, and 4°C), the protein pellet was washed two times with 80% (v/v) acetone, air dried, and hydrolyzed into the amino acids for 12 h (125 µL, 6 m HCl, and 100°C). The hydrolysate was purified (Millipore centrifugal filter units, Ultrafree-MC, Durapore polyvinylidene difluoride, 0.22 µm Merck KGaA). A volume of 50 µL of the hydrolysate was mixed with 50 µL of internal standard (1.2 mm α-aminobutyric acid) and evaporated under a nitrogen stream. Amino acids were derivatized by the addition of 100 µL of N-methyl-N-t-butyldimethylsilyl-trifluoroacetamide (Macherey-Nagel) followed by incubation for 1 h at 80°C. The isotopic composition of the amino acids was quantified by GC-C-IRMS (Trace GC Ultra gas chromatograph and Delta V Plus isotope ratio mass spectrometer; Thermo Scientific). A sample volume of 0.5 µL was injected via the PTV inlet (250°C) at a split ratio of 1:20. Helium was used as a carrier gas at a constant flow rate of 1 mL min−1. Analytes were separated on a fused silica capillary column (HP-5MS, 30 m × 25 mm, 0.25 µm; Agilent) and then transferred to an oxidizing combustion reactor (1,000°C). The initial oven temperature of 120°C was kept for 2 min. Afterward, the temperature was increased at a rate of 8°C min−1 until 200°C. In a second gradient step, the temperature was raised to 300°C at 10°C min−1 followed by a temperature hold for 5 min. The GC-C-IRMS profile of the MBDSTFA-derivatized amino acids was obtained in selective ion monitoring mode via mass isomers of formed CO2 (m/z 44, 45, and 46) and N2 (at m/z 28 and 29) at their corresponding retention times. Metabolite identification was achieved by gas chromatography-mass spectrometry (7890A GC System, 7000 GC/MS Triple Quad, 7693 Autosampler; Agilent Technologies) measurements of single amino acids and their mixture (10 µm each) in full-scan acquisition mode, followed by a NIST mass spectral search (NIST MS search 2.0) and comparison of the chromatographic pattern with the one of the corresponding GC-C-IRMS measurement. Data acquisition and evaluation were conducted using the software Isodat NT (Thermo Scientific). Analytical accurateness was a precondition for further data evaluation. Data points for which peak integrity was corrupted were omitted from graphical data representation.

Calculation of 13C and 15N Enrichment

The δ values (‰) are expressed relative to international standards as:Embedded Image(1)where R is the ratio of 13C/12C or 15N/14N. The 13C and 15N measurements were calibrated against Vienna Pee Dee Belemnite and atmospheric nitrogen, respectively, using the international reference materials cellulose (IAEA-CH-3) and ammonium sulfate (IAEA-N-1) as secondary standards. Typical values for δ13C of unlabeled C3 plant material are between −34‰ and −22‰ (Meier-Augenstein, 1999a; Richter et al., 2010). Enrichment values also were expressed as atomic percent (AP), which is the percentage of 13C or 15N atoms relative to the total amount of carbon or nitrogen atoms in the sample. Atomic percent enrichment was derived via Equation 2:Embedded Image(2)Atomic percent excess (APE), the absolute value for isotopic enrichment, was calculated by subtracting the enrichment of the control from the enrichment of the sample:

Embedded Image(3)

Data Correction for Natural Isotopes

Naturally occurring isotopes of the analyte and of derivative groups were considered (Wittmann, 2007), and data correction following GC-C-IRMS measurement was done as described previously (Metges and Daenzer, 2000; Docherty et al., 2001; Heinzle et al., 2008). Briefly, δ values were normalized to their respective unlabeled equivalents by subtracting the values of the unlabeled control from the corresponding value of the labeled sample:Embedded Image(4)where δcorr is the labeled compound, δsample is the derivatized labeled compound, and δcontrol is the derivatized unlabeled compound. For each experiment, unlabeled control plants that were harvested (at least three biological replicates) were exposed to the exact same breeding conditions as the labeled plants (i.e. they were grown on the same batch of soil or hydroponic medium, respectively). Furthermore, unlabeled controls were subjected to the same sample-processing steps as labeled samples.

For the amino acid pathway illustrations (Fig. 5, A and B), the corrected δ values were normalized to 100%. Therefore, the highest δcorr value of the respective data set was set to 100%. The normalized value of any number x (Xnorm) of the original data set was calculated by the following equation:Embedded Image(5)where δmax was the highest δcorr value.

Determination of Root-to-Shoot Ratio and Translocation Flux

To set up a flux map for a rice seedling, it was important to derive the root-to-shoot ratio of the analyzed plantlets. It was assumed that the decrease of 15N enrichment in the root within 2 h of tracing is only due to the translocation of label to the shoot. With this assumption, the root-to-shoot ratio was derived via the following formula:Embedded Image(6)where M is the mass of shoot and root as indicated. A root:shoot ratio of 1:6 was obtained for 12-d-old seedlings. This value was used to estimate the percentage enrichment of individual plant parts after 2 h of tracing. Considering that shoot biomass was 6 times as much as root biomass, it follows that 15N enrichment of the shoot was diluted by a factor of 6 upon translocation to the shoot, whereas 13C enrichment accumulated 6-fold upon translocation to the root. Accordingly, δ15N values of the shoot were multiplied by 6, whereas δ13C values of the root were divided by 6. Shoot and root enrichment values of 13C as well as 15N labeling, at time point zero, were summed, displaying 100% uptake. On this basis, 13C and 15N percentage enrichments were estimated for root and shoot. The amount of 13C labeling that could not be recovered in plant tissue was assumed to be lost by respiration.

Statistical Analysis

The statistical significance of differences between mean values was determined using Student’s t test or one-way ANOVA followed by a posthoc Tukey’s test. Differences were considered significant when the P value was below 0.05.

Supplemental Data

The following supplemental materials are available.

Acknowledgments

We thank Enrico Peter for input regarding experimental design and troubleshooting; Olaf Woiwode for cultivation of plants, maintenance of equipment, and assistance with the preparation and execution of experiments; as well as Jürgen Kastler and René Müller for C-IRMS analyses and data evaluation.

Footnotes

  • www.plantphysiol.org/cgi/doi/10.1104/pp.15.01217

  • The author responsible for 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: Christoph Wittmann (christoph.wittmann{at}uni-saarland.de).

  • L.M.D. conducted the isotope labeling experiments, assisted in establishment of the GC-IR-MS method, processed and evaluated measurement data, drew all figures, and wrote the article; V.B. contributed to isotope labeling studies; D.R. designed and constructed the labeling reactors and provided technical assistance during isotope labeling studies; C.B., G.M., and K.K. assisted in isotope labeling studies during preliminary layout and testing of the approach; H.B. conducted C-IR-MS and GC-C-IRMS analytics; R.F. contributed to project layout and supervision, experimental design, isotope labeling studies, labeling analytics, data evaluation and processing, and writing of the manuscript; O.E.B. and T.E. provided advice on experimental design and writing of the manuscript; and C.W. processed and evaluated measurement data, conceived and supervised the project, and wrote the manuscript.

  • ↵1 Present address: Sandoz GmbH, 65929 Frankfurt am Main, Germany.

  • ↵2 Present address: Nestlé Suisse S.A., 1814 La Tour-de-Peilz, Switzerland.

  • ↵3 Present address: Evonik Industries AG, 45128 Essen, Germany.

Glossary

MS
mass spectrometry
C-IRMS
combustion-isotope ratio mass spectrometry
EA
elemental analysis
GC
gas chromatography
m/z
mass-to-charge ratio
EMP
Embden-Meyerhof-Parnas
PP
pentose phosphate
  • Received December 11, 2015.
  • Accepted March 9, 2016.
  • Published March 10, 2016.

REFERENCES

  1. ↵
    1. Albacete AA,
    2. Martínez-Andújar C,
    3. Pérez-Alfocea F
    (2014) Hormonal and metabolic regulation of source-sink relations under salinity and drought: from plant survival to crop yield stability. Biotechnol Adv 32: 12–30
    OpenUrlCrossRefPubMed
  2. ↵
    1. Allen DK,
    2. Libourel IGL,
    3. Shachar-Hill Y
    (2009) Metabolic flux analysis in plants: coping with complexity. Plant Cell Environ 32: 1241–1257
    OpenUrlCrossRefPubMed
  3. ↵
    1. Arp WJ
    (1991) Effects of source-sink relations on photosynthetic acclimation to elevated CO2. Plant Cell Environ 14: 869–875
    OpenUrlCrossRef
  4. ↵
    1. Cegelski L,
    2. Schaefer J
    (2005) Glycine metabolism in intact leaves by in vivo 13C and 15N labeling. J Biol Chem 280: 39238–39245
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Chen WP,
    2. Yang XY,
    3. Harms GL,
    4. Gray WM,
    5. Hegeman AD,
    6. Cohen JD
    (2011) An automated growth enclosure for metabolic labeling of Arabidopsis thaliana with 13C-carbon dioxide: an in vivo labeling system for proteomics and metabolomics research. Proteome Sci 9: 9–23
    OpenUrlCrossRefPubMed
  6. ↵
    1. Cliquet JB,
    2. Deléens E,
    3. Mariotti A
    (1990) C and N mobilization from stalk and leaves during kernel filling by C and N tracing in Zea mays L. Plant Physiol 94: 1547–1553
    OpenUrlAbstract/FREE Full Text
  7. ↵
    1. Cock JH,
    2. Yoshida S
    (1972) Accumulation of 14C carbohydrate before flowering and its subsequent redistribution and respiration in the rice plant. Proc Crop Sci Soc Japan 41: 226–234
    OpenUrlCrossRef
  8. ↵
    1. Cramer GR,
    2. Urano K,
    3. Delrot S,
    4. Pezzotti M,
    5. Shinozaki K
    (2011) Effects of abiotic stress on plants: a systems biology perspective. BMC Plant Biol 11: 163
    OpenUrlCrossRefPubMed
  9. ↵
    1. Derrien D,
    2. Balesdent J,
    3. Marol C,
    4. Santaella C
    (2003) Measurement of the 13C/12C ratio of soil-plant individual sugars by gas chromatography/combustion/isotope-ratio mass spectrometry of silylated derivatives. Rapid Commun Mass Spectrom 17: 2626–2631
    OpenUrlCrossRefPubMed
  10. ↵
    1. Derrien D,
    2. Marol C,
    3. Balesdent J
    (2004) The dynamics of neutral sugars in the rhizosphere of wheat: an approach by 13C pulse-labelling and GC/C/IRMS. Plant Soil 267: 243–253
    OpenUrlCrossRef
  11. ↵
    1. Docherty G,
    2. Jones V,
    3. Evershed RP
    (2001) Practical and theoretical considerations in the gas chromatography/combustion/isotope ratio mass spectrometry delta13C analysis of small polyfunctional compounds. Rapid Commun Mass Spectrom 15: 730–738
    OpenUrlCrossRefPubMed
  12. ↵
    1. Dyckmans J,
    2. Flessa H,
    3. Shangguan Z,
    4. Beese F
    (2000) A dual 13C and 15N long-term labelling technique to investigate uptake and translocation of C and N in beech (Fagus sylvatica L.). Isotopes Environ Health Stud 36: 63–78
    OpenUrlCrossRefPubMed
  13. ↵
    1. Fischer R,
    2. Emans N
    (2000) Molecular farming of pharmaceutical proteins. Transgenic Res 9: 279–299
    OpenUrlCrossRefPubMed
  14. ↵
    1. Funayama K,
    2. Kojima S,
    3. Tabuchi-Kobayashi M,
    4. Sawa Y,
    5. Nakayama Y,
    6. Hayakawa T,
    7. Yamaya T
    (2013) Cytosolic glutamine synthetase1;2 is responsible for the primary assimilation of ammonium in rice roots. Plant Cell Physiol 54: 934–943
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Gauthier PPG,
    2. Bligny R,
    3. Gout E,
    4. Mahé A,
    5. Nogués S,
    6. Hodges M,
    7. Tcherkez GGB
    (2010) In folio isotopic tracing demonstrates that nitrogen assimilation into glutamate is mostly independent from current CO2 assimilation in illuminated leaves of Brassica napus. New Phytol 185: 988–999
    OpenUrlCrossRefPubMed
  16. ↵
    1. Goñi MA,
    2. Eglinton TI
    (1996) Stable carbon isotopic analyses of lignin-derived CuO oxidation products by isotope ratio monitoring-gas chromatography-mass-spectrometer (irm-GC-MS). Org Geochem 24: 601–615
    OpenUrlCrossRef
  17. ↵
    1. Griffiths RI,
    2. Manefield M,
    3. Ostle N,
    4. McNamara N,
    5. O’Donnell AG,
    6. Bailey MJ,
    7. Whiteley AS
    (2004) 13CO2 pulse labelling of plants in tandem with stable isotope probing: methodological considerations for examining microbial function in the rhizosphere. J Microbiol Methods 58: 119–129
    OpenUrlCrossRefPubMed
  18. ↵
    1. Hasunuma T,
    2. Harada K,
    3. Miyazawa S,
    4. Kondo A,
    5. Fukusaki E,
    6. Miyake C
    (2010) Metabolic turnover analysis by a combination of in vivo 13C-labelling from 13CO2 and metabolic profiling with CE-MS/MS reveals rate-limiting steps of the C3 photosynthetic pathway in Nicotiana tabacum leaves. J Exp Bot 61: 1041–1051
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Heinzle E,
    2. Yuan Y,
    3. Kumar S,
    4. Wittmann C,
    5. Gehre M,
    6. Richnow HH,
    7. Wehrung P,
    8. Adam P,
    9. Albrecht P
    (2008) Analysis of 13C labeling enrichment in microbial culture applying metabolic tracer experiments using gas chromatography-combustion-isotope ratio mass spectrometry. Anal Biochem 380: 202–210
    OpenUrlCrossRefPubMed
  20. ↵
    1. Hurkman WJ,
    2. Tanaka CK
    (1986) Solubilization of plant membrane proteins for analysis by two-dimensional gel electrophoresis. Plant Physiol 81: 802–806
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Hutchinson CR,
    2. Stephen MT,
    3. Hsia S,
    4. Carver RA
    (1976) Biosynthetic studies with 13CO2 of secondary plant metabolites: Nicotinana alkaloids. 1. Initial experiments. J Am Chem Soc 98: 6006–6011
    OpenUrlCrossRefPubMed
  22. ↵
    1. Jones D,
    2. Carter J,
    3. Eglinton G,
    4. Jumeau E,
    5. Fenwick C
    (1991) Determination of d13C values of sedimentary straight chain and cyclic alcohols by gas chromatography/isotope ratio mass spectrometry. Biol Mass Spectrom 20: 641–646
    OpenUrlCrossRef
  23. ↵
    1. Junker BH,
    2. Lonien J,
    3. Heady LE,
    4. Rogers A,
    5. Schwender J
    (2007) Parallel determination of enzyme activities and in vivo fluxes in Brassica napus embryos grown on organic or inorganic nitrogen source. Phytochemistry 68: 2232–2242
    OpenUrlCrossRefPubMed
  24. ↵
    1. Kato M,
    2. Kobayashi K,
    3. Ogiso E,
    4. Yokoo M
    (2004) Photosynthesis and dry-matter production during ripening stage in a female-sterile line of rice. Plant Prod Sci 7: 184–188
    OpenUrlCrossRef
  25. ↵
    1. Khush G
    (2003) Productivity improvements in rice. Nutr Rev 61: 114–116
    OpenUrlCrossRef
  26. ↵
    1. Kiyomiya S,
    2. Nakanishi H,
    3. Uchida H,
    4. Tsuji A,
    5. Nishiyama S,
    6. Futatsubashi M,
    7. Tsukada H,
    8. Ishioka NS,
    9. Watanabe S,
    10. Ito T, et al.
    (2001) Real time visualization of 13N-translocation in rice under different environmental conditions using positron emitting tracer imaging system. Plant Physiol 125: 1743–1753
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Kruger NJ,
    2. Huddleston JE,
    3. Le Lay P,
    4. Brown ND,
    5. Ratcliffe RG
    (2007) Network flux analysis: impact of 13C-substrates on metabolism in Arabidopsis thaliana cell suspension cultures. Phytochemistry 68: 2176–2188
    OpenUrlCrossRefPubMed
  28. ↵
    1. Kruger NJ,
    2. Ratcliffe RG
    (2009) Insights into plant metabolic networks from steady-state metabolic flux analysis. Biochimie 91: 697–702
    OpenUrlCrossRefPubMed
  29. ↵
    1. Lam H,
    2. Coschigano K,
    3. Schultz C,
    4. Melo-Oliveira R,
    5. Tjaden G,
    6. Ngai N,
    7. Hsieh M,
    8. Coruni G
    (1995) Use of Arabidopsis mutants and genes to study amide amino acid biosynthesis. Plant Cell 7: 887–898
    OpenUrlFREE Full Text
  30. ↵
    1. Lattanzi FA,
    2. Ostler U,
    3. Wild M,
    4. Morvan-Bertrand A,
    5. Decau ML,
    6. Lehmeier CA,
    7. Meuriot F,
    8. Prud’homme MP,
    9. Schäufele R,
    10. Schnyder H
    (2012) Fluxes in central carbohydrate metabolism of source leaves in a fructan-storing C3 grass: rapid turnover and futile cycling of sucrose in continuous light under contrasted nitrogen nutrition status. J Exp Bot 63: 2363–2375
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Leake JR,
    2. Ostle NJ,
    3. Rangel-Castro JI,
    4. Johnson D
    (2006) Carbon fluxes from plants through soil organisms determined by field 13CO2 pulse-labelling in an upland grassland. Appl Soil Ecol 33: 152–175
    OpenUrlCrossRef
  32. ↵
    1. Ma F,
    2. Jazmin LJ,
    3. Young JD,
    4. Allen DK
    (2014) Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation. Proc Natl Acad Sci USA 111: 16967–16972
    OpenUrlAbstract/FREE Full Text
  33. ↵
    1. Makino A,
    2. Mae T,
    3. Ohira K
    (1984) Relation between nitrogen and ribulose-1,5-bisphosphate carboxylase in rice leaves from emergence through senescence. Plant Cell Physiol 25: 429–437
    OpenUrlAbstract/FREE Full Text
  34. ↵
    1. Maliga P,
    2. Graham I
    (2004) Molecular farming and metabolic engineering promise a new generation of high-tech crops. Curr Opin Plant Biol 7: 149–151
    OpenUrlCrossRefPubMed
  35. ↵
    1. Meier-Augenstein W
    (1999a) Applied gas chromatography coupled to isotope ratio mass spectrometry. J Chromatogr A 842: 351–371
    OpenUrlCrossRefPubMed
  36. ↵
    1. Meier-Augenstein W
    (1999b) Use of gas chromatography-combustion-isotope ratio mass spectrometry in nutrition and metabolic research. Curr Opin Clin Nutr Metab Care 2: 465–470
    OpenUrlCrossRefPubMed
  37. ↵
    1. Meier-Augenstein W
    (2002) Stable isotope analysis of fatty acids by gas chromatography-isotope ratio mass spectrometry. Anal Chim Acta 465: 63–79
    OpenUrlCrossRef
  38. ↵
    1. Meng F,
    2. Dungait JAJ,
    3. Zhang X,
    4. He M,
    5. Guo Y,
    6. Wu W
    (2013) Investigation of photosynthate-C allocation 27 days after 13C-pulse labeling of Zea mays L. at different growth stages. Plant Soil 373: 755–764
    OpenUrlCrossRef
  39. ↵
    1. Metges CC,
    2. Daenzer M
    (2000) 13C gas chromatography-combustion isotope ratio mass spectrometry analysis of N-pivaloyl amino acid esters of tissue and plasma samples. Anal Biochem 278: 156–164
    OpenUrlCrossRefPubMed
  40. ↵
    1. Molero G,
    2. Aranjuelo I,
    3. Teixidor P,
    4. Araus JL,
    5. Nogués S
    (2011) Measurement of 13C and 15N isotope labeling by gas chromatography/combustion/isotope ratio mass spectrometry to study amino acid fluxes in a plant-microbe symbiotic association. Rapid Commun Mass Spectrom 25: 599–607
    OpenUrlCrossRefPubMed
  41. ↵
    1. Nogués S,
    2. Tcherkez G,
    3. Cornic G,
    4. Ghashghaie J
    (2004) Respiratory carbon metabolism following illumination in intact French bean leaves using 13C/12C isotope labeling. Plant Physiol 136: 3245–3254
    OpenUrlAbstract/FREE Full Text
  42. ↵
    1. Nouchi I,
    2. Ito O,
    3. Harazono Y,
    4. Kouchi H
    (1995) Acceleration of 13C-labelled photosynthate partitioning from leaves to panicles in rice plants exposed to chronic ozone at the reproductive stage. Environ Pollut 88: 253–260
    OpenUrlCrossRefPubMed
  43. ↵
    1. Olsson PA,
    2. van Aarle IM,
    3. Gavito ME,
    4. Bengtson P,
    5. Bengtsson G
    (2005) 13C incorporation into signature fatty acids as an assay for carbon allocation in arbuscular mycorrhiza. Appl Environ Microbiol 71: 2592–2599
    OpenUrlAbstract/FREE Full Text
  44. ↵
    1. Panetta RJ,
    2. Jahren AH
    (2011) Single-step transesterification with simultaneous concentration and stable isotope analysis of fatty acid methyl esters by gas chromatography-combustion-isotope ratio mass spectrometry. Rapid Commun Mass Spectrom 25: 1373–1381
    OpenUrlCrossRefPubMed
  45. ↵
    1. Peuke AD,
    2. Hartung W,
    3. Jeschke WD
    (1994) The uptake and flow of C, N and ions between roots and shoots in Ricinus communis L. II. Grown with low or high nitrate supply. J Exp Bot 45: 733–740
    OpenUrlAbstract/FREE Full Text
  46. ↵
    1. Ratcliffe RG,
    2. Shachar-Hill Y
    (2006) Measuring multiple fluxes through plant metabolic networks. Plant J 45: 490–511
    OpenUrlCrossRefPubMed
  47. ↵
    1. Rawson BHM,
    2. Hofstra G
    (1969) Translocation and remobilization of 14C assimilated at different stages by each leaf of the wheat plant. Aust J Biol Sci 22: 321–331
    OpenUrl
  48. ↵
    1. Richter EK,
    2. Spangenberg JE,
    3. Kreuzer M,
    4. Leiber F
    (2010) Characterization of rapeseed (Brassica napus) oils by bulk C, O, H, and fatty acid C stable isotope analyses. J Agric Food Chem 58: 8048–8055
    OpenUrlCrossRefPubMed
  49. ↵
    1. Roessner-Tunali U,
    2. Liu J,
    3. Leisse A,
    4. Balbo I,
    5. Perez-Melis A,
    6. Willmitzer L,
    7. Fernie AR
    (2004) Kinetics of labelling of organic and amino acids in potato tubers by gas chromatography-mass spectrometry following incubation in 13C labelled isotopes. Plant J 39: 668–679
    OpenUrlCrossRefPubMed
  50. ↵
    1. Roitsch T
    (1999) Source-sink regulation by sugar and stress. Curr Opin Plant Biol 2: 198–206
    OpenUrlCrossRefPubMed
  51. ↵
    1. Römisch-Margl W,
    2. Schramek N,
    3. Radykewicz T,
    4. Ettenhuber C,
    5. Eylert E,
    6. Huber C,
    7. Römisch-Margl L,
    8. Schwarz C,
    9. Dobner M,
    10. Demmel N, et al.
    (2007) 13CO2 as a universal metabolic tracer in isotopologue perturbation experiments. Phytochemistry 68: 2273–2289
    OpenUrlCrossRefPubMed
  52. ↵
    1. Rontein D,
    2. Dieuaide-Noubhani M,
    3. Dufourc EJ,
    4. Raymond P,
    5. Rolin D
    (2002) The metabolic architecture of plant cells: stability of central metabolism and flexibility of anabolic pathways during the growth cycle of tomato cells. J Biol Chem 277: 43948–43960
    OpenUrlAbstract/FREE Full Text
  53. ↵
    1. Roy SJ,
    2. Negrão S,
    3. Tester M
    (2014) Salt resistant crop plants. Curr Opin Biotechnol 26: 115–124
    OpenUrlCrossRefPubMed
  54. ↵
    1. Royuela M,
    2. Gonzalez A,
    3. Gonzalez EM,
    4. Arrese-Igor C,
    5. Aparicio-Tejo PM,
    6. Gonzalez-Murua C
    (2000) Physiological consequences of continuous, sublethal imazethapyr supply to pea plants. J Plant Physiol 157: 345–354
    OpenUrlCrossRef
  55. ↵
    1. Sasakawa H,
    2. Yamamoto Y
    (1978) Comparison of the uptake of nitrate and ammonium by rice seedlings: influences of light, temperature, oxygen concentration, exogenous sucrose, and metabolic inhibitors. Plant Physiol 62: 665–669
    OpenUrlAbstract/FREE Full Text
  56. ↵
    1. Scarponi L,
    2. Alla MMN,
    3. Martinetti L
    (1995) Consequences on nitrogen metabolism in soybean (Glycine max L.) as a result of Imazethapyr action on acetohydroxy acid synthase. J Agric Food Chem 43: 809–814
    OpenUrlCrossRef
  57. ↵
    1. Schaefer J,
    2. Kier LD,
    3. Stejskal EO
    (1980) Characterization of photorespiration in intact leaves using carbon dioxide labeling. Plant Physiol 65: 254–259
    OpenUrlAbstract/FREE Full Text
  58. ↵
    1. Schwender J
    (2008) Metabolic flux analysis as a tool in metabolic engineering of plants. Curr Opin Biotechnol 19: 131–137
    OpenUrlCrossRefPubMed
  59. ↵
    1. Schwender J,
    2. Ohlrogge JB,
    3. Shachar-Hill Y
    (2003) A flux model of glycolysis and the oxidative pentosephosphate pathway in developing Brassica napus embryos. J Biol Chem 278: 29442–29453
    OpenUrlAbstract/FREE Full Text
  60. ↵
    1. Shachar-Hill Y
    (2013) Metabolic network flux analysis for engineering plant systems. Curr Opin Biotechnol 24: 247–255
    OpenUrlCrossRefPubMed
  61. ↵
    1. Shaner DL,
    2. Reider ML
    (1986) Physiological responses of corn (Zea mays) to AC 243,997 in combination with valine, leucine, and isoleucine. Pest Biochem Physiol 25: 248–257
    OpenUrlCrossRef
  62. ↵
    1. Shaner DL,
    2. Singh B
    (1991) Imidazolinone-induced loss of acetohydroxyacid synthase activity in maize is not due to the enzyme degradation. Plant Physiol 97: 1339–1341
    OpenUrlAbstract/FREE Full Text
  63. ↵
    1. Sharma AK,
    2. Sharma MK
    (2009) Plants as bioreactors: recent developments and emerging opportunities. Biotechnol Adv 27: 811–832
    OpenUrlCrossRefPubMed
  64. ↵
    1. Sharp RE,
    2. Poroyko V,
    3. Hejlek LG,
    4. Spollen WG,
    5. Springer GK,
    6. Bohnert HJ,
    7. Nguyen HT
    (2004) Root growth maintenance during water deficits: physiology to functional genomics. J Exp Bot 55: 2343–2351
    OpenUrlAbstract/FREE Full Text
  65. ↵
    1. Szecowka M,
    2. Heise R,
    3. Tohge T,
    4. Nunes-Nesi A,
    5. Vosloh D,
    6. Huege J,
    7. Feil R,
    8. Lunn J,
    9. Nikoloski Z,
    10. Stitt M, et al.
    (2013) Metabolic fluxes in an illuminated Arabidopsis rosette. Plant Cell 25: 694–714
    OpenUrlAbstract/FREE Full Text
  66. ↵
    1. Tan S,
    2. Evans RR,
    3. Dahmer ML,
    4. Singh BK,
    5. Shaner DL
    (2005) Imidazolinone-tolerant crops: history, current status and future. Pest Manag Sci 61: 246–257
    OpenUrlCrossRefPubMed
  67. ↵
    1. Tanaka A,
    2. Osaki M
    (1983) Growth and behavior of photosynthesized 14C in various crops in relation to productivity. Soil Sci Plant Nutr 29: 147–158
    OpenUrlCrossRef
  68. ↵
    1. Tanaka A,
    2. Yamaguchi J
    (1968) The growth efficiency in relation to the growth of the rice plant. Soil Sci Plant Nutr 14: 110–116
    OpenUrlCrossRef
  69. ↵
    1. Tcherkez G,
    2. Cornic G,
    3. Bligny R,
    4. Gout E,
    5. Ghashghaie J
    (2005) In vivo respiratory metabolism of illuminated leaves. Plant Physiol 138: 1596–1606
    OpenUrlAbstract/FREE Full Text
  70. ↵
    1. Tcherkez G,
    2. Nogués S,
    3. Bleton J,
    4. Cornic G,
    5. Badeck F,
    6. Ghashghaie J
    (2003) Metabolic origin of carbon isotope composition of leaf dark-respired CO2 in French bean. Plant Physiol 131: 237–244
    OpenUrlAbstract/FREE Full Text
  71. ↵
    1. Thrower SL
    (1962) Translocation of labelled assimilates in the soybean. Aust J Biol Sci 15: 629–649
    OpenUrl
  72. ↵
    1. Tresch S
    (2013) Strategies and future trends to identify the mode of action of phytotoxic compounds. Plant Sci 212: 60–71
    OpenUrlCrossRefPubMed
  73. ↵
    1. Turgeon R
    (1989) The sink-source transition in leaves. Annu Rev Plant Physiol Plant Mol Biol 40: 119–138
    OpenUrlCrossRef
  74. ↵
    1. Wang H,
    2. Zhang M,
    3. Guo R,
    4. Shi D,
    5. Liu B,
    6. Lin X,
    7. Yang C
    (2012) Effects of salt stress on ion balance and nitrogen metabolism of old and young leaves in rice (Oryza sativa L.). BMC Plant Biol 12: 194
    OpenUrlCrossRefPubMed
  75. ↵
    1. Williams TCR,
    2. Miguet L,
    3. Masakapalli SK,
    4. Kruger NJ,
    5. Sweetlove LJ,
    6. Ratcliffe RG
    (2008) Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions. Plant Physiol 148: 704–718
    OpenUrlAbstract/FREE Full Text
  76. ↵
    1. Wilson JB
    (1988) A review of evidence on the control of shoot:root ratio, in relation to models. Ann Bot (Lond) 61: 433–449
    OpenUrlAbstract/FREE Full Text
  77. ↵
    1. Wittmann C
    (2007) Fluxome analysis using GC-MS. Microb Cell Fact 6: 6
    OpenUrlCrossRefPubMed
  78. ↵
    1. Wu WX,
    2. Liu W,
    3. Lu HH,
    4. Chen YX,
    5. Medha D,
    6. Janice T
    (2009) Use of 13C labeling to assess carbon partitioning in transgenic and nontransgenic (parental) rice and their rhizosphere soil microbial communities. FEMS Microbiol Ecol 67: 93–102
    OpenUrlAbstract/FREE Full Text
  79. ↵
    1. Yang X,
    2. Römheld V,
    3. Marschner H
    (1994) Effect of bicarbonate on root growth and accumulation of organic acids in Zn-inefficient and Zn-efficient rice cultivars (Oryza sativa L.). Plant and Soil 164: 1–7
    OpenUrlCrossRef
  80. ↵
    1. Yoshida S
    (1981) Fundamentals of Rice Crop Science. International Rice Research Institute. Los Baños, Philippines
  81. ↵
    1. Young JD,
    2. Shastri AA,
    3. Stephanopoulos G,
    4. Morgan JA
    (2011) Mapping photoautotrophic metabolism with isotopically nonstationary 13C flux analysis. Metab Eng 13: 656–665
    OpenUrlCrossRefPubMed
  82. ↵
    1. Yousfi S,
    2. Serret MD,
    3. Araus JL
    (2013) Comparative response of δ13C, δ18O and δ15N in durum wheat exposed to salinity at the vegetative and reproductive stages. Plant Cell Environ 36: 1214–1227
    OpenUrlCrossRef
  83. ↵
    1. Yousfi S,
    2. Serret MD,
    3. Márquez AJ,
    4. Voltas J,
    5. Araus JL
    (2012) Combined use of δ¹³C, δ18O and δ15N tracks nitrogen metabolism and genotypic adaptation of durum wheat to salinity and water deficit. New Phytol 194: 230–244
    OpenUrlCrossRefPubMed
  84. ↵
    1. Zhu C,
    2. Zhu J,
    3. Cao J,
    4. Jiang Q,
    5. Liu G,
    6. Ziska LH
    (2014) Biochemical and molecular characteristics of leaf photosynthesis and relative seed yield of two contrasting rice cultivars in response to elevated [CO₂]. J Exp Bot 65: 6049–6056
    OpenUrlAbstract/FREE Full Text
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Novel Approach for High-Throughput Metabolic Screening of Whole Plants by Stable Isotopes
Lisa Maria Dersch, Veronique Beckers, Detlev Rasch, Guido Melzer, Christoph Bolten, Katina Kiep, Horst Becker, Oliver Ernst Bläsing, Regine Fuchs, Thomas Ehrhardt, Christoph Wittmann
Plant Physiology May 2016, 171 (1) 25-41; DOI: 10.1104/pp.15.01217
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