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. 2017 Jun 14;174(4):2261–2273. doi: 10.1104/pp.17.00610

Variation in Leaf Respiration Rates at Night Correlates with Carbohydrate and Amino Acid Supply1,[OPEN]

Brendan M O’Leary a,b,2, Chun Pong Lee a, Owen K Atkin b, Riyan Cheng b, Tim B Brown b, A Harvey Millar a
PMCID: PMC5543967  PMID: 28615345

Mature Arabidopsis leaves display substantial variation in nighttime respiration rates that is metabolically linked to daytime carbon and nitrogen assimilation but not to nighttime protein synthesis.

Abstract

Plant respiration can theoretically be fueled by and dependent upon an array of central metabolism components; however, which ones are responsible for the quantitative variation found in respiratory rates is unknown. Here, large-scale screens revealed 2-fold variation in nighttime leaf respiration rate (RN) among mature leaves from an Arabidopsis (Arabidopsis thaliana) natural accession collection grown under common favorable conditions. RN variation was mostly maintained in the absence of genetic variation, which emphasized the low heritability of RN and its plasticity toward relatively small environmental differences within the sampling regime. To pursue metabolic explanations for leaf RN variation, parallel metabolite level profiling and assays of total protein and starch were performed. Within an accession, RN correlated strongly with stored carbon substrates, including starch and dicarboxylic acids, as well as sucrose, major amino acids, shikimate, and salicylic acid. Among different accessions, metabolite-RN correlations were maintained with protein, sucrose, and major amino acids but not stored carbon substrates. A complementary screen of the effect of exogenous metabolites and effectors on leaf RN revealed that (1) RN is stimulated by the uncoupler FCCP and high levels of substrates, demonstrating that both adenylate turnover and substrate supply can limit leaf RN, and (2) inorganic nitrogen did not stimulate RN, consistent with limited nighttime nitrogen assimilation. Simultaneous measurements of RN and protein synthesis revealed that these processes were largely uncorrelated in mature leaves. These results indicate that differences in preceding daytime metabolic activities are the major source of variation in mature leaf RN under favorable controlled conditions.

Few plant metabolic fluxes are readily accessible to routine measurement. The major exceptions to this are fluxes involving gas exchange, such as respiration and photosynthesis. Measurements of respiratory gas exchange (i.e. mitochondrial oxygen uptake or CO2 release in the absence of photorespiration) are useful from a metabolic perspective because they can be interpreted in terms of the underlying carbon fluxes and the generation of ATP by oxidative phosphorylation (Sweetlove et al., 2013). The biochemical reactions of respiration that produce CO2 and lead to oxygen consumption are well understood (Plaxton and Podestá, 2006; Sweetlove et al., 2010; Millar et al., 2011; Tcherkez et al., 2012). The stoichiometries of the reactions and the connections between them are known, which provides us with a metabolic map of respiration that includes glycolysis, the oxidative pentose phosphate pathway, the citric acid cycle, the mitochondrial electron transport chain (mETC), ATP synthase, and several other surrounding reactions. In plants, carbohydrates are the dominant respiratory substrates, whereas lipids are rarely respired (Plaxton and Podestá, 2006). Carbohydrate oxidation proceeds via organic acids, which serve many purposes in plant cells. Two metabolic fates for organic acids are intimately linked to respiration: (1) further oxidation to CO2 via the citric acid cycle, providing reductant to the mETC and fueling oxidative phosphorylation; and (2) the provision of carbon skeletons needed for the assimilation of nitrogen into amino acids. Because the metabolic pathways supporting ATP production and carbon skeleton production for amino acid biosynthesis largely overlap, respiration is considered to be fulfilling both functions simultaneously in plants. How these two processes are regulated to meet changing cellular demands and integrated diurnally with photosynthesis (carbon reduction) lies at heart of understanding plant primary carbon metabolism.

As an easily measurable metabolic flux, determining how variation in rates of leaf respiration is linked to genetics, development, metabolite levels, and enzymes activities is also an opportunity to better predict rates of carbon use in plants. Determinants of respiration have been widely studied in plants, motivated by the need to (1) better understand plant growth and performance in variable environments; (2) model plant growth in managed and natural ecosystems; and (3) predict the impact of future climate change on carbon exchange between vegetation and the atmosphere (Leakey et al., 2009). The fraction of daily fixed carbon respired is substantial (varying from 20% to 80%, depending on the species), with around half of whole-plant respiration taking place in leaves (Atkin et al., 2007). Thus, variations in the rate of leaf respiration are quantitatively important, not only for individual plants but also for issues such as the speed and scale of future climate warming. Because of this, variations in respiration need to be accounted for in model frameworks, including those designed to model crop and natural ecosystem metabolic fluxes. Currently in such models, respiration is commonly predicted as a scalar of photosynthesis or nitrogen content (Ryan, 1991; Cannell and Thornley, 2000; Reich et al., 2008; Atkin et al., 2015). However, the causal mechanisms of these relationships are not well described, nor are they thought to adequately capture the complex 16-fold variation in respiration rate observed from leaves of differing genetic, environmental, and developmental backgrounds (Wright et al., 2004, 2006; Reich et al., 2008; Atkin et al., 2015). Importantly, much of the total variation in leaf respiration persists among cooccurring species within one environmental site (Atkin et al., 2015), suggesting that genetics strongly determines respiratory flux. Understanding the mechanistic basis of genotypic and environmental variability in leaf respiration is needed if the predictive capacity of crop/natural ecosystem models is to be improved.

The conceptualization of variation of respiration in plants typically leads to the proposal that changes in respiratory rate are due primarily to an altered supply of substrates or an altered demand for respiratory products, namely ATP and carbon skeletons (Cannell and Thornley, 2000; Noguchi, 2005). Changes in environment also can cause an adjustment (i.e. acclimation) of total respiratory capacity (Leakey et al., 2009). However, respiratory metabolism is not thought to be limited by enzyme capacity at warm temperatures in vivo because the respiration of harvested tissue or isolated mitochondria can be stimulated to run faster (Atkin and Tjoelker, 2003). The demands on respiration often are categorized by the terms growth or maintenance respiration (Thornley, 1970, 2011; Amthor, 2000) to help conceptualize the different usage of respiratory-derived ATP for macromolecule biosynthesis in growing versus full-grown tissues. However, the subdivision of ATP usage in any form suffers from a difficulty in making any confirmatory empirical measurements. This is especially troublesome in plants, where the ATP yield from respiration can vary dramatically depending on the relative activity of cytochrome versus alternative pathways in the mETC (Millar et al., 2011). Furthermore, the demands that can be placed upon respiration are not distributed equally throughout the night and day (Cannell and Thornley, 2000). For example, in leaves, the energy costs closely associated with nitrogen assimilation and amino acid synthesis are mostly borne by photosynthesis in the day, and protein synthesis also is greater during the day (Matt et al., 2001; Pal et al., 2013). Overall, more rigorous experimentation involving novel lines of empirical evidence is needed to support the advancement in modeling plant respiration and quantitatively assessing its determinants.

For this study, we have specifically chosen to study leaf respiration rates at night (RN), rather than dark respiration rates (Rd) measured during the day under artificial darkness. Arabidopsis (Arabidopsis thaliana) leaves undergo diurnal cycles of carbohydrate, amino acid, and organic acid accumulation, and leaf primary metabolism is strongly regulated in a diurnal fashion. Therefore, it is likely a source of error to consider that the metabolic status underlying Rd measurements is representative of true nighttime metabolism (Florez-Sarasa et al., 2012). No extensive measurement of leaf nighttime metabolic fluxes (e.g. metabolic flux analysis) has been performed; however, Cheung et al. (2014) proposed a model based on flux balance analysis to reconcile observations from day and night leaf metabolism. From the model and much additional research, the following examples of important features of leaf nighttime metabolism can be deduced. First, nighttime respiration is thought to function largely in an energy-generating capacity involving a cyclic flux through the citric acid cycle (Sweetlove et al., 2010; Cheung et al., 2014). Second, leaves continuously export Suc and amino acids throughout the diurnal cycle to support the growth of heterotrophic tissues at a substantial cost of ATP (Bouma et al., 1995; Kallarackal et al., 2012). Third, the assimilation of nitrogen and, thus, de novo amino acid synthesis at night is reduced greatly in leaves because nitrate reduction is low to nil and ammonium assimilation also is less than in daytime (Canvin and Atkins, 1974; Matt et al., 2001; Nelson et al., 2014). Finally, nighttime metabolism appears to be synchronized to the amount of carbohydrate (e.g. starch) stored during the day, such that when demand is sufficient, starch reserves are metabolized evenly through the night and set to be nearly exhausted at dawn (Graf et al., 2010). What is not clear, however, is how the above factors combine to account for the often-reported variation in respiratory rates seen in controlled environment- and field-based studies (Atkin et al., 2015).

Cellular respiration measurements in plants have traditionally been performed using oxygen electrodes to measure oxygen consumption or infrared gas analyzers to measure CO2 evolution. Mass spectrometry-based measurements also are performed and have a particular use in analyzing oxygen isotope discrimination by the cytochrome versus the alternative pathways of the mETC (Cheah et al., 2014). Although providing robust measurements of respiration, these procedures are not high throughput, and this has limited the scope of experiments aimed at better understanding plant respiration. Recently, fluorometric oxygen sensors have been utilized in multiplexed experiments to measure changes in oxygen concentration in solution (Sew et al., 2013) and in gas phase (Scafaro et al., 2017). Here, our study used high-throughput fluorometric measurements to perform large-scale surveys of leaf RN among Arabidopsis accession populations grown under a common favorable environment. We evaluate the contribution of genetic, environmental, and developmental differences to the observed variation in respiration rates. By coupling RN measurements to an extensive metabolomic analysis, we analyzed key patterns of metabolite correlation with and stimulation of RN and discuss the degree to which substrate supply or output demand drives variation in leaf respiration at night.

RESULTS

Diurnal and Developmental Standardization of Leaf Tissue Selection

The technical requirements for a robust high-throughput oxygen consumption rate measurement are linearity with time, a high signal-to-noise ratio, and rapid sample preparation. Oxygen consumption measurements of leaf discs performed in air by the Q2 fluorophore-based oxygen sensor satisfy these requirements. Figure 1A shows a representative oxygen consumption curve for a vial containing three Arabidopsis leaf discs (1 cm2 total) harvested at night and an empty control vial. From 0.5 to at least 3 h after sealing the vials, oxygen depletion was essentially linear with time; therefore, this time span was selected for future gas-phase respiration measurements. Experiments relying on exogenous chemical additions utilized vials containing single leaf discs floated on top of respiration buffer. In the absence of added metabolites, these measurements also were linear with time between 0.5 and 3 h (Fig. 1B). The addition of the respiratory inhibitors cyanide and salicylhydroxamic acid (SHAM; 0.4 and 20 mm, respectively) reduced leaf oxygen consumption by 90% ± 1% (n = 12; Fig. 1C). Therefore, the oxygen depletion within the measurement vials was assumed to be due almost entirely to leaf respiration and will henceforth be referred to as RN.

Figure 1.

Figure 1.

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Representative measurements of leaf oxygen consumption rate. A and B, Measurements of oxygen depletion from leaf discs in air (A) and on top of respiration buffer solution (B) are shown in black; empty sealed control vials are shown in gray. Leaf oxygen consumption between 0.5 and 3 h after sealing the vial is linear, and the coefficient of determination is indicated. C, Measurement of leaf disc oxygen consumption before and after opening the vials for the addition of cyanide (CN) and SHAM to the respiration buffer.

To minimize the diurnal and developmental variation of RN in our screens, we standardized the leaf tissue to be harvested routinely. As shown previously, Arabidopsis leaf respiration rates were significantly higher if the leaf discs contained the midvein but otherwise were similar across the rest of the leaf blade (Supplemental Fig. S1; Sew et al., 2013). Therefore, all experiments used leaf discs excised from either side of the midvein. Arabidopsis leaf RN also varied throughout development, gradually decreasing with leaf age (Supplemental Fig. S1). Leaf selection was standardized by harvesting from the youngest four leaves that had reached the outside edge of each rosette (e.g. leaves 7–10 in Supplemental Fig. S1). Lastly, a time-course experiment was performed to assess variation in RN throughout the night (Fig. 2). Leaf disc samples harvested from the Arabidopsis accession Landsberg erecta, but not Col-0, showed significant differences in RN between a maximum at 6 h and a minimum 10 to 12 h into the 16-h night. However, in both cases, RN was relatively stable between 1 and 4 h into the night. Therefore, leaf tissues were harvested routinely between 2 and 4 h into the dark period, and our RN measurements were assumed to be independent of sampling time.

Figure 2.

Figure 2.

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Time course of respiration measurements throughout the night period. Five replicate measurements each containing three leaf discs from different leaves of Landsberg erecta (black circles) or Columbia-0 (Col-0; gray squares) were taken at the indicated time points throughout the night. Error bars indicate se, and the asterisk and brackets indicate significant differences between time points (P < 0.05).

Screens of Respiration Rates and Growth Rate in Arabidopsis Natural Accessions

A sequence of three independent respiration screens was performed on Arabidopsis plants grown under common favorable conditions in single growth cabinets to minimize environmental variation. Accession screen 1 and accession screen 2 both involved collections of Arabidopsis accessions, while the third Col-0 screen included only the accession Col-0 (for details of the accessions included within each screen, see “Materials and Methods” and Supplemental Table S1). In each screen, four sets of leaf discs from four mature leaves from each harvested plant were assayed for RN (Table I). Directly afterward, the fresh mass of each set of leaf discs was measured. Test measurements performed before and after the approximately 3-h period of RN measurement showed that leaf disc fresh mass did not change significantly during this time (data not shown). Subsequently, total soluble protein content for each set of leaf discs was measured. The mean values for each plant were calculated, and the correlations between plant mean values within each screen are summarized in Table I. The observed area-based rates of RN approximated a normal distribution (Shapiro-Wilk; P > 0.05) and exhibited a 2.3-, 2-, and 2-fold range between the highest and lowest respiring plants in the accession screens 1 and 2 and the Col-0 screen, respectively. There was a consistent positive correlation between area-based rates of RN and protein amount.

Table I. Summary data from the screens of Arabidopsis leaf RN.

Significant correlations between the plant mean values are indicated in boldface (P < 0.01).

Parameter Col-0 Screen Accession Screen 1 Accession Screen 2
Plants sampled 41 226 190
Genotypes sampled 1 226 162
Mean oxygen consumption rate ± sd (µmol m−2 s−1) 0.59 ± 0.09 0.58 ± 0.09 0.76 ± 0.10
Mean oxygen consumption rate ± sd (nmol g−1 s−1) 3.4 ± 0.5 3.5 ± 0.6 3.6 ± 0.5
Correlation coefficients (r)
Oxygen consumption rate per area versus fresh mass 0.17 0.16 0.35
Oxygen consumption rate per area versus protein amount 0.60 0.55 0.58
Fresh mass versus protein amount 0.36 0.10 0.31
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Several findings support the view that the variation in RN observed in the screens was mostly not due to genetic differences among accessions. In accession screen 2, two ecotypes were highly replicated, Col-0 (n = 17) and Ag-0 (n = 11). By comparing the distribution of RN measurements within and between accessions, the heritability of area-based and mass-based RN under the growth conditions of our screen was estimated to be 0.29 and 0.3, respectively, indicating the proportion of variation due to genetic differences. Furthermore, there was low reproducibility of the relative respiratory performance of genotypes across the two accession screens: there was no correlation among area- or mass-based RN values or the relative rank of matching accession measurements between accession screens 1 and 2. A genome-wide association study to examine the causal genetic loci was performed for both screens. However, they did not identify any significant genetic loci as determinants of RN, likely due to a lack of power given the small degree of heritability of the trait. Lastly, the Col-0 screen, which does not include genetic variation, displays a similar overall level of variation in RN to screens 1 and 2 (Table I).

The rate of change in total plant leaf area also was captured by photography during the first 35 d of growth in accession screen 2. Beyond 35 d, leaf overlap within and between pots precluded calculations of total leaf area. Notwithstanding changes occurring between the dates of measurement, there were no strong correlations (r2 > 0.05) between area-based rates of RN and total leaf area, leaf area expansion rate, or relative leaf area expansion rate (Supplemental Table S2).

Metabolite Levels Correlate Strongly with RN

To evaluate the relationship between metabolite levels and RN, metabolomic analyses were performed on leaf disc samples that matched those used in each respiration screen. A subset of 80 plants in screens 1 and 2 were chosen to reflect the range of RN observed. Twenty-one plants were selected from the Col-0 screen. From each plant, four samples of leaf discs were subjected to targeted gas chromatography-mass spectrometry (GC-MS) metabolite analysis, and the relative metabolite abundance data were averaged for each plant and log transformed. Many metabolite levels correlated positively with area-based rates of RN, and the highest correlations observed from each screen are shown in Table II. The full data set of metabolites and correlations is shown in Supplemental Table S3. Most metabolite-RN correlations were stronger in the Col-0 screen, which indicated that intraspecies Arabidopsis genetics affected some metabolite-RN relationships. However, there were obvious similarities across screens, as several metabolites, in particular Ala, pyro-Glu, Glu, Gln, Suc, and gluconic acid, were consistently among the strongest correlating compounds from each screen. Note that pyro-Glu is formed from the cyclization of either Glu or Gln and, thus, represents a combination of these amino acids. No significant negative correlations (r < −0.25) were identified in accession screens 1 and 2, but in the Col-0 screen, three unidentified compounds (likely disaccharides or trisaccharides) showed significant negative correlations with RN (Supplemental Table S3).

Table II. Identified metabolites detected by GC-MS that correlate most strongly with RN.

Coefficients of determination (r2) between averaged leaf disc metabolite levels and RN per area are given. Metabolites with significant correlations and coefficients of determination larger than r2 = 0.2 in any one screen are listed. All correlations are positive. Statistically significant correlations (P < 0.01) are indicated in boldface. n.d., Not detected.

Metabolite Coefficients of Determination
Col-0 Screen Accession Screen 1 Accession Screen 2
Amino acids
 l-Ala 0.53 0.36 0.42
 l-Asp 0.34 0.18 0.34
 Pyro-Glu 0.62 0.12 0.27
 l-Gln 0.61 0.20 n.d.
 l-Glu 0.49 0.16 0.27
 l-Thr 0.28 0.24 0.20
 Gly 0.45 0.11 0.07
 l-Val 0.02 0.15 0.28
 β-Ala 0.24 0.02 0.28
Dicarboxylic acids
 l-Malic acid 0.49 0.01 0.22
 Succinic acid 0.62 0.04 0.16
 Fumaric acid 0.30 0.01 0.02
Carbohydrates and related
 d-Gluconic acid 0.40 0.18 0.31
 Suc 0.49 0.28 0.31
 6-Phosphogluconic acid 0.49 n.d. n.d.
 Maltose 0.48 0.04 0.14
 l-Threonic acid 0.34 0.01 0.05
 l-Ascorbic acid 0.08 0.03 0.25
 Hexose phosphate n.d. 0.12 0.22
Phenolics
 Shikimic acid 0.61 0.02 0.32
 Salicylic acid 0.64 n.d. 0.02
Fatty acids
 Octadecanoic acid 0.44 0.03 0.14
 Hexadecanoic acid 0.44 0.01 0.11
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The amino acid Ala displayed the most consistently strong correlation with RN across all screens (Table I; Fig. 3). Ala levels often are considered to be tightly linked with pyruvate levels via Ala aminotransferase (Miyashita et al., 2007). However, correlations between Ala and RN were consistently much stronger than the correlations between pyruvate and RN, thus indicating a disequilibrium or distinct subcellular localization between pyruvate and Ala pools in the leaf cells (Fig. 3; Supplemental Table S3).

Figure 3.

Figure 3.

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Ala, pyruvate, and starch correlations with RN within and among accessions. A to D, Relative leaf disc levels of Ala and pyruvate as measured by GC-MS are plotted against RN per area. Averaged values per plant from accession screen 2 (A and C) and the Col-0 screen (B and D) are shown. E and F, Starch levels (Glc equivalents) as measured by enzyme assay are plotted against RN per area. Plant averaged values are taken from accession screen 1 (E) and the Col-0 screen (F).

As the major storage carbohydrate in Arabidopsis leaves, it was also of interest to determine the relationship between starch and RN. Starch assays were performed on sets of four replicate leaf samples from each of 57 plants from accession screen 1 and 41 plants of the Col-0 screen. Starch levels among Col-0 plants during the early night correlated strongly with RN (r2 = 0.73; Fig. 3), whereas, among different accessions, starch levels were only weakly correlated with RN (r2 = 0.07).

Using multiple linear regression analysis, it was calculated that protein and Ala amounts were consistently the two strongest predictors of RN in the interaccession screens, and, together with fresh mass, they explained 63% and 65% of the variation in screens 1 and 2, respectively (P < 0.001). In the Col-0 screen, starch was the strongest single metabolic predictor of RN, while Ala was the most significant additional predictor, increasing the variation explained to 80%. However, in all cases, rigorous interpretation of the multiple linear regression analysis was not possible because of the high amounts of covariance among metabolite, starch, and protein levels.

Exogenous Substrates Can Rapidly Stimulate Leaf Respiratory Rate

The strong correlations of some metabolites with RN could be related to substrate supply. Therefore, we tested whether exogenous addition of metabolites could stimulate RN in Arabidopsis leaf discs. Respiratory oxygen consumption measurements were performed as above, but with single leaf discs of the accession Col-0 floating on 10 or 100 mm buffered metabolite solution (Fig. 4). At the high 100 mm exogenous substrate concentration, many but not all metabolites tested had a stimulatory effect on oxygen consumption, including several amino acids, carbohydrates, and organic acids. At the lower concentration of 10 mm, no metabolites displayed a significant stimulation of RN. Incubations with external nitrogen sources consisting of 10 mm KNO3 or 1 to 10 mm NH4Cl also were performed but had no significant effect on RN (Fig. 4). For selected metabolites of interest, additional concentrations also were assayed (Supplemental Fig. S2). These results clearly demonstrate that some metabolites have a concentration-dependent stimulatory effect on nighttime leaf oxygen consumption. No metabolite solution included in the study displayed oxygen consumption in the absence of leaf tissue, and all metabolite solutions were sensitive to the respiratory inhibitors cyanide and SHAM, indicating that any stimulation of oxygen depletion was mostly attributable to RN. As differences in metabolite uptake rate or endogenous metabolite levels were not accounted for, comparisons between metabolite stimulatory effects were not performed.

Figure 4.

Figure 4.

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Screen of the effects of exogenous metabolites on leaf disc RN. Chemical additions to the respiration buffer were made at 10 mm (gray bars) and 100 mm (black bars) for each compound except for KNO3 and NH4Cl, which were made at 10 mm. Values are expressed relative to untreated controls. The compounds are generally sorted as carbohydrates and glycolytic intermediates (A), organic acids (B), amino acids (C), and inorganic nitrogen (D). Asterisks denote significant differences (P < 0.05) between treatments and nontreated controls.

The Uncoupler FCCP Rapidly Stimulates Night Respiration Rate

Compounds that dissipate the electrochemical proton gradient across the mitochondrial inner membrane (known as uncouplers) have frequently been used to assess whether the oxygen consumption rate is limited by being coupled to the oxidative phosphorylation of ADP to ATP by ATP synthase. Here, the uncoupler FCCP stimulated Arabidopsis leaf RN in a rapid and concentration-dependent manner (Fig. 5). This stimulation indicates that limited ADP supply to ATP synthase contributes to restricting the respiration rate (often referred to as adenylate control of respiration). In the presence of 2 µm FCCP, the addition of 100 mm stimulatory metabolites led to significant further stimulations of respiration in all cases tested except for Ala (Fig. 5). Ser and Thr were not significantly stimulatory on their own or in the presence of FCCP. Compounds that increase respiration in the presence of FCCP likely act upstream of the mETC, either as respiratory substrates or activators of oxidative metabolism. Conversely, the initial stimulation of respiration by 100 mm Ala in the absence of FCCP appears to be due to effects downstream of the mETC, presumably by increasing ATP turnover.

Figure 5.

Figure 5.

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FCCP stimulates leaf RN. A, The mitochondrial uncoupler FCCP was supplied exogenously at several concentrations to single leaf discs. The average relative rates of oxygen consumption are shown from a minimum of six replicates, and significant increases compared with control assays (P < 0.05; ANOVA) are indicated by asterisks. B, Leaf discs in the presence of 2 µm FCCP were assayed for respiration in the presence or absence of 100 mm select metabolites. The relative increase caused by the metabolite additions over measurements with FCCP alone are shown, and asterisks indicate significant increases (P < 0.05; paired Student’s t test; n ≥ 6).

The Relationship between RN and Protein Synthesis

We used cycloheximide, an inhibitor of cytosolic ribosomal translation, to evaluate the role of protein synthesis in determining RN. However, the results were uninterpretable, as cycloheximide on its own stimulated RN in a time- and concentration-dependent fashion (Supplemental Fig. S3). This effect of cycloheximide has been documented previously in certain tissues, but the mechanism is unknown (Ellis, 1970; McMahon, 1975).

Instead, further investigations into the relationship between nighttime protein synthesis and respiration were performed by measuring oxygen consumption of leaf discs floating on respiration buffer containing 1 µm [14C]Leu (0.1 µCi). The incorporation of exogenous radiolabeled [14C]Leu into protein, which occurred during the respiration assay, was taken as a simultaneous measure of protein synthesis rate. Averaged measurements of four leaf disc samples from 24 mature leaves of different Col-0 plants revealed that there was only a weak positive correlation between respiration and protein synthesis (Fig. 6). Young developing Arabidopsis leaves are known to have higher rates of protein synthesis per area than mature leaves (Ishihara et al., 2015), which is thought to contribute to higher rates of respiration. In a comparison between developing and mature leaves from the accession Col-0, the simultaneous measurements clearly revealed that developing leaf blade tissue has higher rates of both protein synthesis and respiration (Fig. 6).

Figure 6.

Figure 6.

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Simultaneous measurement of protein synthesis and RN in leaf discs. Net oxygen depletion and dissociations per minute (DPM) from scintillation counts of [14C]Leu incorporation into protein were determined following a 4-h incubation of leaf discs. A, Relationship between RN and [14C]Leu incorporation within mature leaves. Each data point represents the average of four leaf disc measurements taken from a single mature leaf. The coefficient of determination of the linear regression is indicated. B, Measurements from individual leaf discs from young developing leaves (gray circles) and mature leaves (black squares) are compared.

DISCUSSION

Substantial Variation in Leaf Respiratory Rates Is Maintained in a Common Environment

The respiratory flux of leaves can be expected to vary depending on the environment, tissue, developmental stage, time of day, and the species being studied (Atkin et al., 2015). We have sought to limit as many of these factors as possible in order to consider the role of metabolic determinants under controlled, nonstressful conditions. We identified and attempted to eliminate variation in respiration that was associated with time of night, leaf blade location, and leaf developmental stage. We did not detect a correlation between the total leaf area expansion rate for a plant and the respiratory rate of its developed leaf blades, suggesting that variations in shoot growth rate do not have a direct effect on the respiratory rates of mature leaves. However, unintended differences in the growth rate of individual leaves, which were not captured by our total plant growth measurements, remain a possible source of variation in RN. The final 2-fold variation in mature leaf blade RN observed among Arabidopsis accessions was only weakly associated with genetic differences and, thus, could be mostly reproduced in a genetically uniform population of Col-0 plants. The low heritability of RN determined here (0.31) is consistent with previous low measures of leaf respiration heritability in Hordeum spontaneum (Poorter et al., 2005). In comparison, a much greater amount of the variation could be linked to metabolic status, which provides a distinct perspective on the source of variation in RN.

Correlations between Carbon Substrates and RN

Respiration often has been described as being driven by substrate supply or ATP demand (Cannell and Thornley, 2000). Using simple chemical and substrate treatments of leaf discs, we could show that, contrary to some previous observations (Noguchi, 2005; Li et al., 2013), leaf RN was stimulated rapidly in situ by both high levels of several carbon substrates and the uncoupler FCCP (Figs. 4 and 5). Thus, it is experimentally possible to demonstrate in situ the control of respiration by both substrate supply and adenylate restriction. However, the effect of substrate supply on respiration was concentration dependent, and it is probable that the levels of some exogenous metabolites needed to promptly stimulate respiration are not encountered in vivo. Furthermore, not all compounds that stimulated RN necessarily acted solely as respiratory substrates. For example, stimulation by Ala was sensitive to the uncoupler FCCP, indicating that Ala stimulates ATP consumption. Nevertheless, as the stimulations of many potential substrates were qualitatively additive to the stimulation caused by FCCP (Fig. 5), the conclusion remains that Arabidopsis leaf RN, in practice, can be stimulated by substrate supply.

In the early night, following a day of favorable photosynthetic conditions, carbohydrates and organic acids are plentiful and constitute the main stores of carbon fueling RN (Plaxton and Podestá, 2006). Robust correlations between carbohydrates and RN have been observed several times previously, following experiments that subjected plants to varying photosynthetic conditions during the preceding light period (Azcon-Bieto et al., 1983; Noguchi, 2005; Florez-Sarasa et al., 2012; Peraudeau et al., 2015). In addition to starch, Arabidopsis plants also accumulate the dicarboxylic acids fumarate and malate during the day (Pracharoenwattana et al., 2010). Here, following relatively uniform photosynthetic conditions, we also observed that stored carbon substrates for respiration, like starch, the starch breakdown product maltose, malate, and to a lesser extent fumarate, all are strongly correlated with RN and could explain the bulk of variation in RN among Col-0 plants. The levels of succinate, fumarate, and malate displayed strong covariance with starch (r2 = 0.72, 0.63, and 0.5 respectively; Supplemental Table S3), which likely results because of their mutual dependence of photosynthetic carbon fixation (Pracharoenwattana et al., 2010). Suc also displays a consistent correlation with RN; however, Suc is unlikely to represent a major respiratory substrate in leaves, because it is actively synthesized and exported from leaves at night and the respiration of newly synthesized Suc would invoke a wasteful (futile) cycle of ATP hydrolysis, although it may still occur to some degree. Rather, Suc synthesis and export represents a substantial ATP cost borne by leaves at night, previously estimated to account for 29% of leaf Rd (Bouma et al., 1995). Therefore, a strong case can be made that RN variation is largely related to photosynthetically produced substrate availability, and this is discussed below in the context of diurnal metabolism.

Protein Synthesis Is Not a Major Determinant of Mature Arabidopsis Leaf RN

The metabolite group that correlated most strongly and consistently with RN across all screens consisted of the major (i.e. abundant) amino acids: Glu, Asp, Ala, Gln, and Thr. Through our experiments, we can evaluate three possible causal reasons for these correlations: substrate supply, allosteric regulation, and respiratory costs associated with amino acids.

First, amino acids in leaves are not known to be oxidized for respiration except during carbon starvation or senescence (Hildebrandt et al., 2015). Given that stores of starch and organic acids remain at early points in the night, it is unlikely that amino acids would represent major substrates for the night respiration measurements performed in this study. Second, amino acids also can act as potent allosteric regulators of respiratory enzymes. In particular, Glu and Asp are potent allosteric effectors of the key regulatory glycolytic enzymes phosphoenolpyruvate carboxylase and cytosolic pyruvate kinase. However, the pattern of known regulatory effects of Asp and Glu and other amino acids on respiratory enzymes would not explain the consistently positive correlation of amino acids with RN (O’Leary and Plaxton, 2015). Third, there may be respiratory costs associated with amino acids: specifically, rates of (1) amino acid synthesis, (2) amino acid export, or (3) protein metabolism. In leaves, the rate of inorganic N assimilation into amino acids and the associated costs of ATP and carbon skeletons are reduced at night compared with the daytime. This is because NO3− assimilation is not thought to occur at night and NH4+ assimilation is sharply reduced, greatly limiting the capacity for de novo amino acid synthesis (Canvin and Atkins, 1974; Matt et al., 2001; Nelson et al., 2014). In our study, neither exogenous NO3− nor NH4+ stimulated nighttime oxygen consumption, which is consistent with inorganic N not being appreciably assimilated and amino acid synthesis costs being limited (Fig. 4). As source tissues, mature leaves continually export amino acids to sink tissues, but the export rate and the indirect ATP cost of amino acid transport from leaves that occur at night have not been quantified, and experimental methods to address this question are lacking (Kallarackal et al., 2012). Therefore, it remains unclear whether this process is a cost that contributes greatly to the observed variation in RN. Lastly, protein synthesis and degradation continue at night in plant leaves and are thought to represent major cellular demands for respiratory ATP production (Bouma et al., 1994; Cannell and Thornley, 2000; Pal et al., 2013). However, the correlation between RN and protein synthesis observed here within mature leaves was weak (Fig. 6), indicating that variation in protein synthesis is not a major determinant of the variation in RN. This suggests that, in our target mature Arabidopsis leaves, protein synthesis is a comparatively minor sink for ATP consumption at night. This is consistent with recent measurements of proteome-wide turnover rates in Arabidopsis leaves, which estimated protein biosynthesis costs to account for 13% of the ATP budget in mature leaves and up to 38% in actively growing leaves (Li et al., 2016). Altogether, within our current understanding of leaf nighttime metabolism, we find no compelling rationale to conclude that the relationship between major amino acid levels and Arabidopsis RN is causative in mature leaves.

An alternative explanation to the above is that the correlation between major amino acids and RN is indirect and not causal. The major amino acids may reflect other metabolic activities that are themselves determinants of RN. Relative to other amino acids, the major amino acids Glu, Asp, Ala, Gln, Ser, and Gly are thought to exist as single metabolically active pools that are closely linked to primary metabolism (Nelson et al., 2014; Ishihara et al., 2015). For example, the Ala pool is the most rapidly and completely labeled amino acid pool following 13CO2 or 15NH4 application to photosynthesizing Arabidopsis or barley (Hordeum vulgare) leaves (Szecowka et al., 2013; Nelson et al., 2014; Ishihara et al., 2015). Therefore, major amino acids could display a strong correlation with RN as a result of the sensitivity of their pool size to changes in both C and N assimilation. As total free amino acids accumulate during the light period and are depleted during the night period in Arabidopsis and tobacco (Nicotiana tabacum; Fritz et al., 2006; Gibon et al., 2006; Watanabe et al., 2014), amino acid levels in the early night, not unlike starch, could be an indicator of the previous day’s aggregate metabolic activity (Fig. 7).

Figure 7.

Figure 7.

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Model depicting how aspects of day metabolism are involved in the variation of RN under a common environment in mature leaves. Dashed boxes represent metabolic processes, while solid boxes represent metabolite pools and protein. Where measured, coefficients of determination between aspects of metabolism and RN are shown. Inputs into day assimilatory metabolism, shown as thick arrows, are assumed to be constant. Major amino acids and carbohydrate stores are known to accumulate during the day and become depleted during the night. Stored carbohydrates are linked to export and respiration, with Suc levels indicative of carbohydrate export. Nighttime major amino acid pools are linked to protein synthesis and export, but the costs associated with amino acid export are unknown. The correlation observed with protein is attributed mostly to a relationship between protein and daytime assimilatory capacity, as the correlation between RN and protein synthesis is low. Organic acid metabolism and other metabolic processes are omitted for simplicity but may be quantitatively important in determining respiration.

RN Scales with Daytime Metabolic Activity

Respiration has been observed previously to scale with photosynthesis. A link with daytime metabolic productivity also may partly explain the consistent correlation between respiration and N content, which itself is thought to reflect protein content. The protein-respiration correlation has been attributed to (1) protein levels scaling with metabolic activity, in particular photosynthesis, and (2) increased protein turnover costs to maintain higher amounts of protein (Ryan, 1991; Bouma et al., 1995; Reich et al., 2008). In our study, we found the correlation between RN and protein content in mature leaves to be much stronger than that between RN and protein synthesis. This suggests that the scaling of protein amount with metabolic activity underlies the correlation between RN and protein (or N) in mature leaves (Fig. 7).

The metabolic correlations observed here between RN and protein, carbon stores, and amino acid levels all support a model where increased daytime assimilatory activity is responsible for the variation in RN in mature leaves. As summarized in Figure 7, increased daytime C and N assimilation is linked mechanistically to RN most obviously by increased Suc export costs at night (the costs of amino acid export being unknown). The ATP costs associated with Suc export have been estimated to account for a wide range of total RN output, with an estimated average of 29% (Bouma et al., 1995). Here, the levels of Suc, starch, and major amino acids, which relate to assimilation activity, and protein, which relates to assimilation capacity, could explain most of the variation in RN, while protein synthesis predicted very little. Hence we hypothesize that differences in export costs, driven by differences in the availability of exportable nutrients, may be the main source of variation in RN in mature leaves. Ultimately, the proposed variation in assimilatory activity within leaf blade tissue may be due to small differences in environmental conditions such as light or N supply.

RN Supports Biosynthesis

We do not exclude the possibilities that other ATP-consuming processes also may influence RN or that substrate supply directly enhances respiratory oxygen consumption to some extent. Indeed, the observed correlations between shikimic acid, a precursor of plastidic aromatic metabolism, hexadecanoic acid and octadecanoic acid, products of plastidic fatty acid synthesis and intermediates of glycerolipid synthesis, and gluconic acid/6-phosphogluconate, an intermediate in the NADPH-generating pentose phosphate pathway, all suggest a relation between RN and biosynthetic pathways. However, nonphotosynthetic aspects of plastid biosynthesis, like fatty acid synthesis and the shikimate pathway, also are down-regulated at night (Sasaki et al., 1997; Entus et al., 2002), and whether any remaining flux through these pathways would represent a substantial nocturnal ATP cost is not known. An alternative explanation is that fatty acids and shikimate covary strongly with other products of plastid daytime metabolism, like starch, whose levels more directly influence RN (Supplemental Table S3).

Lastly, the correlation between RN and the plant signaling compound salicylic acid is intriguing, but we can only speculate about the reason for this relationship. Mechanistically, at low levels, salicylic acid has been observed to uncouple respiration, activate succinate dehydrogenase in isolated mitochondria, and up-regulate alternative oxidase expression (Norman et al., 2004; Belt et al., 2017). Salicylic acid has long been known to be involved in controlling thermogenic respiration in Arum spp. (Raskin et al., 1987), and the strong correlation obtained here suggests that it could affect the rate of nonthermogenic plant respiration.

CONCLUSION

There has long been known to be a diversity of respiration rates throughout the plant kingdom. An important finding of this study was that the extent of intraspecies variation in RN of mature leaves remained sizable even under a favorable controlled environment. A combination of high-throughput measurements provided a fresh experimental approach and new empirical data that quantitatively assess underlying metabolic reasons for this variation. The genetic interaction with respiration is undoubtedly complex, given the size of the pathway, but under the standard test conditions used here, it accounts for a rather small amount of natural intraspecies variation of RN. These results suggest that differences in mature leaf RN relate largely to a combination of daytime metabolic activities and associated nighttime export costs and less so to nighttime protein synthesis rates. As such, variation in leaf RN should not be viewed as a question of supply and demand, because both respiratory substrates and export costs depend on assimilated carbohydrate levels. Rather, RN in mature leaves should be viewed as scaling with daytime metabolism (Fig. 7). This concept provides a more mechanistic basis for the known scaling of RN with photosynthesis, but our results also indicate that daytime N assimilation into amino acids, besides C assimilation into carbohydrates, could be quantitatively important in explaining or predicting RN. More research into the nighttime use of amino acids in leaves is needed to further mechanistically understand this relationship.

MATERIALS AND METHODS

Plant Growth

Arabidopsis (Arabidopsis thaliana) seeds were sown into a 3:1:1 mix of potting soil, perlite, and vermiculite, supplemented with slow-release fertilizer, and covered with a transparent plastic cover until established. Plants were grown in a controlled-environment growth chamber maintaining a short-day photoperiod of 8 h of light and 16 h of dark (11 pm to 7 am light), a photon flux of 150 µmol m−2 s−1, a relative humidity of 75%, and a day/night temperature cycle of 22°C/17°C. Soil was kept well moistened with regular watering. Unless indicated otherwise, leaf tissue was harvested from 5- to 7-week-old plants as described for the respiration screen below.

Arabidopsis Respiration Screens

Three different night respiration screens were performed. Accession screens 1 and 2 were performed on sets of plants from an Arabidopsis natural accession collection (Li et al., 2010) grown in a single growth chamber. In accession screen 1, 226 plants were sampled, each a single replicate of a separate natural accession. Our decision to use a single plant for each accession was motivated by the need to assess as wide a range of intraspecies genotypic variation in RN as possible. Following the completion of the first screen, we decided to perform a second screen using a growth cabinet with in-built photographic capabilities, enabling the assessment of plant growth rate; however, this required switching from fluorescent to LED lighting. In screen 2, 190 plants were sampled, representing 162 singly replicated accessions and 17 and 11 replicate plants of the accessions Col-0 and Ag-0, respectively, which were used to estimate the heritability of RN. The lists of accessions sampled in screens 1 and 2 are provided in Supplemental Table S1, with 86 accessions being sampled in both screens. Following the completion of screen 2, a third screen was performed to focus on intragenotype variation in RN. Screen 3 was performed in a different growth cabinet with fluorescent lighting, and 41 plants of the accession Col-0 were harvested.

For all screens, seeds were pretreated with 10 µm GA3 for 7 d at 4°C to encourage uniform germination. Between 37 and 46 d after sowing, four leaves were harvested from plants selected at the time of harvesting on the basis of leaf size (approximately 6 cm2). No leaf senescence had begun at the time of harvesting in any of the plants. The leaves chosen from each plant were carefully selected to represent the four youngest leaves that had reached the outer edge of the rosette. Importantly, under the growth conditions used, mature Arabidopsis leaves continue slowly expanding, thus eliminating the possibility of using fully expanded leaves as the standard.

Leaf tissue was harvested 2 to 4 h into the night under dim green light (less than 1 µmol photons m−2 s−1). Tissue harvest was completed using a 6.5-mm diameter cork borer to punch six leaf discs from each leaf, equaling 2 cm2 of leaf blade. Three discs (1 cm2) were used for the oxygen consumption measurement (see below), followed by fresh mass measurement, then snap frozen in liquid N2 and stored for protein measurements. The other three discs were immediately snap frozen in liquid N2 and stored at −80°C for metabolite analysis.

Respiration Measurements

Respiration measurements were performed on a Q2 oxygen sensor (Astec-Global) in sealed 850-µL capacity tubes containing three leaf discs totaling 1 cm2. Oxygen concentration measurements were made at 3-min intervals. The slope of oxygen consumption was calculated between 0.5 and 3 h after the start of the run. Standards containing normal air and 100% N2 were used to calibrate to 100% and 0% atmospheric oxygen. The oxygen partial pressure was determined to be 20.95% atmospheric pressure, and the ideal gas law was used to calculate molar oxygen consumption rates (Scafaro et al., 2017).

To test the effect of metabolite additions, single leaf discs harvested at 4 h into the night period were floated on top of 600 µL of respiration buffer (50 mm HEPES, 10 mm MES, pH 6.6, and 200 µm CaCl2) with or without additional metabolites within an 850-µL volume tube. To allow time for metabolite uptake, respiration measurements were calculated as the slope between 1 and 3 h after the start of the run. A minimum of five leaves from different plants were assayed for each treatment.

Genome-Wide Association Study

Genome-wide association studies of respiration per leaf area and respiration per fresh mass were performed as described previously (Cheng et al., 2010). The 0.05 genome-wide threshold was determined using the Bonferroni method, which proved to be close to the empirical threshold found using the permutation test (Churchill and Doerge, 1994).

Leaf Area Expansion Measurements

Leaf area expansion was measured using the TraitCapture imaging and segmentation pipeline (Brown et al., 2014). Images with a resolution of approximately 25 pixels mm−2 were captured with two Canon EOS700D, DSLR digital cameras mounted in the center of each side of the chamber about 1.5 m from the plants. Images were corrected for color and distortion and then segmented using the TraitCapture segmentation code to calculate leaf area for each plant at each time point.

Metabolite Analysis

Frozen leaf discs were ground in a bead mill, and metabolites were immediately extracted in 200 µL of 85% (v/v) methanol, 15% distilled, deionized water, and 8 µg mL−1 ribitol as an internal standard. Samples were incubated on a thermomixer for 15 min at 60°C and 1,400 rpm, followed by centrifugation for 10 min at 20,000g. For starch assays, the pellet was further washed with ethanol and assayed for starch as described previously (Smith and Zeeman, 2006). For GC-MS metabolite analysis, the supernatant was transferred to a new tube and centrifuged for 5 min at 20,000g. Exactly 40 µL of supernatant was transferred to a glass vial and dried in a vacuum concentrator without heat.

Samples were derivatized by incubation in 10 µL of 20 mg mL−1 methoxyamine hydrochloride in pyridine for 90 min at 37°C with agitation at 750 rpm, followed by the addition of 15 µL of N-methyl-N-(trimethylsilyl)trifluoroacetamide and incubation at 37°C for 30 min with agitation at 750 rpm. Next, 5 µL of alkane standard was added to each sample. In screen 2 but not screen 1, sample derivatization was performed online using a Gerstel sample preparation robot.

Metabolites were fractionated and detected using an Agilent 7890A gas chromatograph, equipped with a Varian CP9013-Factor 4 column (40 m × 0.25 µm i.d.), coupled to an Agilent 5975 quadrupole mass spectrum detector. Helium acted as the carrier gas at a constant flow rate of 1 mL min−1. The injection temperature was 250°C; the transfer line and ion source were set at 250°C. The oven temperature was increased constantly at 15°C min−1 from 70°C to 325°C. After a solvent delay of 5 min, mass spectra were recorded at 50 Hz with a scanning range of 40 to 600 m/z. GC-MS data were analyzed using MetabolomeExpress (https://www.metabolome-express.org; Carroll et al., 2010).

Protein Quantification

Frozen leaf discs were ground in a bead mill, mixed with 500 µL of 50 mm HEPES, pH 8, 0.1% (v/v) Triton X-100, and 1% (w/v) polyvinylpolypyrrolidone, and processed again in the bead mill. Samples were centrifuged for 10 min at 20,000g, and 200 µL of supernatant was transferred to a new tube, snap frozen in liquid N2, and stored at −80°C. Protein quantification was performed using a BCA protein assay kit (Bio-Rad) following the manufacturer’s instructions.

Protein Synthesis Quantification

Relative protein synthesis rates were measured using a modified version of a published method (Van der Werf et al., 1992). Radiolabeled Leu is used as a protein synthesis indicator, as the 14C label from Leu is not rapidly metabolized into other metabolites besides protein (Van der Werf et al., 1992). Leaf discs harvested at 2 h into the night period were floated on top of 400 µL of respiration buffer containing 0.1 µCi of uniformly labeled [14C]Leu (300 mCi mmol−1; Perkin Elmer) for 4 h in sealed Q2 respiration vials. Directly afterward, leaf discs were rinsed and then frozen in liquid N2. Leaf discs were ground in a bead mill, and protein was extracted with 200 µL of 0.1 m NaOH for 15 min at 65°C and 1,400 rpm. Following centrifugation at 20,000g for 15 min, the supernatant was collected and the pellet was reextracted by the same method. The combined supernatants were precipitated with 5% TCA at 4°C overnight to precipitate protein but not free [14C]Leu. The samples were centrifuged for 15 min at 20,000g, and the pellet was washed with acid ethanol (0.1 m HCl:ethanol = 1:11 [v/v]). The pellet was resolubilized in 0.1 m NaOH containing 0.5% SDS and mixed with 5 mL of Ultima Gold (Perkin Elmer) followed by scintillation counting.

Supplemental Data

The following supplemental materials are available.

Acknowledgments

We thank Dr. Adam Carroll (Australian National University) for assistance in analyzing the metabolomics data using MetabolomeExpress and Dr. Clarissa Alves Negrini, Dr. Andrew Scafaro, Yuzhen Fan, and Matthew Spence (Australian National University) for assistance with respiration measurements.

Glossary

mETC

mitochondrial electron transport chain

Col-0

Columbia-0

GC-MS

gas chromatography-mass spectrometry

Footnotes

1

This work was supported by the Australian Research Council Centre of Excellence in Plant Energy Biology (grant no. CE140100008). B.M.O. is supported by an Australian Research Council DECRA Fellowship (grant no. DE150100130).

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