Proton exchange by the vacuolar nitrate transporter CLCa is required for plant growth and nitrogen use efficiency

Abstract

Nitrate is a major nutrient and osmoticum for plants. To deal with fluctuating nitrate availability in soils, plants store this nutrient in their vacuoles. Chloride channel a (CLCa), a 2${\text{NO}}_3^{-}$/1H⁺ exchanger localized to the vacuole in Arabidopsis (Arabidopsis thaliana), ensures this storage process. CLCa belongs to the CLC family, which includes anion/proton exchangers and anion channels. A mutation in a glutamate residue conserved across CLC exchangers is likely responsible for the conversion of exchangers to channels. Here, we show that CLCa with a mutation in glutamate 203 (E203) behaves as an anion channel in its native membrane. We introduced the CLCa_E203A point mutation to investigate its physiological importance into the Arabidopsis clca knockout mutant. These CLCa_E203A mutants displayed a growth deficit linked to the disruption of water homeostasis. Additionally, CLCa_E203A expression failed to complement the defect in nitrate accumulation of clca and favored higher N-assimilation at the vegetative stage. Further analyses at the post-flowering stages indicated that CLCa_E203A expression results in an increase in N uptake allocation to seeds, leading to a higher nitrogen use efficiency compared to the wild-type. Altogether, these results point to the critical function of the CLCa exchanger on the vacuole for plant metabolism and development.

The conversion of the nitrate/proton exchanger CLCa into a nitrate channel in Arabidopsis plants reduces water contents in planta but increases nitrogen use efficiency.

In a nutshell.

Background: Nitrogen is quantitatively the most important inorganic nutrient for plants. Roots mainly take nitrogen up in the form of nitrate (${\text{NO}}_3^{-}$). Once inside the cells, ${\text{NO}}_3^{-}$ can be assimilated into amino acids or stored in the vacuole, where it regulates cell water content to sustain plant growth. CLCa is the main transporter mediating the entry of ${\text{NO}}_3^{-}$ into vacuoles. It works as an exchanger removing one proton (H⁺) from the vacuole to store two ${\text{NO}}_3^{-}$ anions. CLCa belongs to a conserved family composed of both anion/proton exchangers and anion channels, with closely similar structures. Most of the exchangers share a conserved glutamate residue (E203 in CLCa).

Question: Is the ${\text{NO}}_3^{-}$/H⁺ exchange mechanism of CLCa required for plants to stabilize water and nitrate status? What are the physiological consequences of converting CLCa from an exchanger to a nitrate channel?

Findings: We generated Arabidopsis thaliana lines that express a form of CLCa in which the amino acid E203 is mutated, turning this protein into a ${\text{NO}}_3^{-}$ channel. This modification decreases nitrate accumulation in the vacuole and increases amino acids and protein synthesis, thereby leading to high N content in the seeds. Although these plants have higher nitrogen use efficiency (NUE), their growth is reduced, in association with a diminution of water content. This finding reveals the importance of the CLCa exchange mechanism in allowing plant cells to maintain cell turgor irrespective of fluctuating nitrogen concentrations in the soil.

Next steps: We would like to investigate the possibility of selecting plants with higher NUE without affecting growth, through root-specific expression of the mutated version of CLCa. Decreasing ${\text{NO}}_3^{-}$ accumulation in roots should stimulate ${\text{NO}}_3^{-}$ translocation to the shoot, without disturbing the water content in aerial parts.

Introduction

Plants face frequent environmental fluctuations that challenge their survival, growth, and reproduction. Fluctuating nutrient availability is one of the major factors limiting plant growth. Among these nutrients, nitrate is the major form of inorganic nitrogen taken up by plants in aerobic soil. As a critical nutrient for plant development, nitrate is applied extensively in agriculture to sustain yields. However, because soil clay–humus complexes only weakly retain nitrate, it is easily leached, thereby leading to severe environmental pollution (Strahm and Harrison, 2006). Therefore, one current challenge of plant breeding is to generate crop varieties with improved nitrogen use efficiency (NUE) to reduce excessive effluents in rivers and underground water.

Nitrate is absorbed by the roots and translocated to the shoot (Cookson et al., 2005; Dechorgnat et al., 2011). Once inside the cells, its assimilation occurs through the combined actions of different enzymes: nitrate reductase (NR) converts the nitrate into nitrite, which is reduced into ammonium by nitrite reductase. The ammonium is then incorporated into amino acids through the glutamine synthetase/glutamate synthase cycle. At the cellular level, plants are able to adjust their cytosolic nitrate concentrations between 1 and 6 mM according to nitrate availability in the environment (Cookson et al., 2005; Miller and Smith, 2008; Demes et al., 2020). The regulation of nitrate assimilation is essential for achieving such homeostasis. In parallel, the vacuolar compartment also plays a key role in the fine-tuning of cytosolic nitrate concentrations. When the external concentrations of nitrate are high, plants store it in their vacuoles, from which it can be remobilized when the demand increases, such as during a starvation period (Martinoia et al., 1981; Miller and Smith, 2008). To accumulate nitrate at high concentrations in the vacuole, active transport is required (Miller and Smith, 1992). An early study suggested that this transport is mediated by an antiporter energized by vacuolar proton pumps generating a pH gradient through the vacuolar membrane (Schumaker and Sze, 1987). Such a vacuole-localized 2${\text{NO}}_3^{-}$/H⁺ exchanger called CLCa was characterized by electrophysiological measurements on isolated Arabidopsis (Arabidopsis thaliana) vacuoles (De Angeli et al., 2006). A knockout (KO) mutant of CLCa (clca-2) displays a decrease in the endogenous nitrate content by up to 50%, supporting its major role in nitrate storage in the vacuole (De Angeli et al., 2006). Consequently, the reduced CLCa activity in this mutant leads to an increase in nitrate assimilation and a change in root nitrate influx to adjust cytosolic nitrate homeostasis (Monachello et al., 2009; Liao et al., 2018).

It is assumed that nitrate in the vacuole not only ensures nitrate homeostasis and proper plant growth under starvation but also plays a role as an osmoticum involved in plant water homeostasis (McIntyre, 1997). Genetic approaches support this hypothesis, as quantitative trait loci for nitrate and water contents under nonlimiting nitrogen conditions co-localize (Loudet et al., 2003). The CLCa gene is highly expressed in mesophyll cells and stomata. In the clca-2 KO mutant, stomatal opening in response to light and closure in response to abscisic acid (ABA) is impaired, suggesting that CLCa is involved in anion translocation through the vacuolar membrane in both directions, depending on environmental conditions. Consequently, the clca-2 mutant is highly sensitive to hydric stress compared to wild-type plants (Wege et al., 2014), supporting the central function of CLCa in regulating water content.

CLCa is a member of a highly conserved protein family that is widely present from prokaryotes to mammals (Mindell and Maduke, 2001). Although most CLCs are more selective for chloride, CLCa mainly transports nitrate, as its selectivity motif contains a proline instead of the serine found in other characterized CLC exchangers (De Angeli et al., 2006; Wege et al., 2010). Additionally, despite their close structural similarity, CLC family members can be either anion channels or anion/proton exchangers. In humans, five CLCs are chloride/proton exchangers (HsCLC3–7), whereas the four others are chloride channels (HsCLC1, HsCLC2, HsCLCΚa, and HsCLCΚb) (Poroca et al., 2017). Interestingly, most of the exchangers share a highly conserved glutamate residue (E203 in CLCa), called the gating glutamate. This residue, initially identified in CLC-ec1 from Escherichia coli (Dutzler et al., 2002), is located in CLC’s selectivity filter and projects its side chain in the ion pathway. When deprotonated, this residue blocks anion transport but, upon protonation, it moves out of the pathway, thereby allowing anion access (Dutzler et al., 2003; Park et al., 2017). During a protonation/deprotonation cycle of this residue, two anions can be transported by the exchanger. The mutation of this glutamate to a residue that cannot be protonated in bacteria (CLC-ec1), human (CLC-3, CLC-5, and CLC-7) (Novarino et al., 2010; Weinert et al., 2010; Costa et al., 2012; Weinert et al., 2020), and plant CLCs (CLCa) (Bergsdorf et al., 2009) uncouples anion transport from proton transport and converts the exchanger into a channel.

In mammals, both CLC exchangers and channels coexist (Poroca et al., 2017). Interestingly, CLC transporters are all localized to intracellular compartments, whereas CLC channels are restricted to the plasma membrane. In Arabidopsis, all CLCs are localized to intracellular compartments and, so far, no CLC channel has been identified. In addition to CLCa, three other CLCs are located in the vacuolar membrane in A. thaliana. Among these, AtCLCb, the closest homolog of CLCa, is also a 2${\text{NO}}_3^{-}$/H⁺ exchanger (Lv et al., 2009; von der Fecht-Bartenbach et al., 2010). Nevertheless, KO mutants for AtCLCb contain as much nitrate as the wild-type genotype, suggesting that CLCa compensates for the loss of AtCLCb (von der Fecht-Bartenbach et al., 2010). The other vacuolar CLCs in Arabidopsis, AtCLCc and AtCLCg, are involved in chloride transport, as the KO mutants are more sensitive to NaCl stress than the wild-type, but their electrophysiological properties are currently unknown (Jossier et al., 2010; Nguyen et al., 2016).

CLCa is thus an essential transporter for nitrate storage in the vacuole and the control of water content. As an exchanger mechanism was demonstrated for CLCa, we wondered if the coupling of nitrate and proton transport is absolutely required for plants to stabilize water and nitrate status. We investigated this question by analyzing the physiological consequences of the conversion of the CLCa exchanger into a channel. We mutated the sequence encoding the gating glutamate of CLCa into an alanine, a residue that cannot be protonated (E203A), and introduced it into a KO clca background to analyze the phenotypes of the generated plants for water content and NUE. Identifying the physiological consequences of such a mutation provides insight into the significance of CLCa functioning as an exchanger rather than a channel.

Results

Expression of CLCa with a gating glutamate mutation in clca KO plants

To analyze the physiological consequences of the E203A mutation in CLCa, we introduced CLCa_E203A under the control of the 35S promoter or the CLCa native promoter into the clca-2 KO mutant background (De Angeli et al., 2006). As a positive control, we used the complemented line clca-2/35S:CLCa, which was already characterized in previous studies (Wege et al., 2010, 2014) and two clca-2/pCLCa:CLCa control lines generated in this study. clca-2/35S:CLCa_E203A lines 3 and 8 (L3 and L8) were selected because they overexpress CLCa as strongly as clca-2/35S:CLCa complemented plants (20- to 40-fold relative to the wild-type [Ws-2]), whereas the clca-2/pCLCa:CLCa_E203A L1 and L4 and clca-2/pCLCa:CLCa L6 and L2 were selected because they display an expression level 0.5- to two-fold compared to native CLCa in the Ws-2 background (Supplemental Figure S1A). In parallel, we examined whether the mutation in CLCa would alter the subcellular localization of this protein by transforming the clca-2 mutant with clca-2/35S:GFP-CLCa_E203A. Fluorescence was observed in the guard cells and apical root cells of plants from two independent lines (Supplemental Figure S1B). As expected, the mutated form of CLCa localized to the vacuolar membrane in both cell types.

CLCa_E203A shows reduced proton/anion coupling

A previous report showed that in Xenopus laevis oocytes, the “gating glutamate” mutation E203A in the CLCa exchanger disrupted ${\text{NO}}_3^{-}$/H⁺ coupling (Bergsdorf et al., 2009). Therefore, to quantify the changes in vacuolar anion transport induced by the E203A mutation in CLCa, we investigated the properties of the ion currents across mesophyll vacuolar membranes from clca-2/35S:CLCa_E203A L3 and L8 (Figure 1). We applied the patch-clamp technique to vacuoles from these two genotypes as well as clca-2/35S:CLCa, Ws-2, and the clca-2 KO mutant in the whole-vacuole configuration. In order to measure anionic currents only, we used the nonpermeable cation BisTrisPropane as a counter ion. clca-2/35S:CLCa_E203A L3 and L8 had similar behaviors (Figure 1A compared to Supplemental Figure S2A); thus, for detailed characterization, we focused on clca-2/35S:CLCa_E203A L3. In order to evaluate the impact of the E203A mutation on the H⁺/${\text{NO}}_3^{-}$ coupling of CLCa and the intensity of ${\text{NO}}_3^{-}$ currents across the tonoplast in the different transgenic lines, we used the experimental design shown in Figure 1A. First, we exposed vacuoles to bi-ionic conditions (i.e. ${\text{NO}}_3^{-}$ in the vacuole, Cl⁻ on the cytosolic side) to measure the vacuolar current densities in the different genotypes. Second, vacuoles were exposed to ${\text{NO}}_3^{-}$ in the cytosol (i.e. with ${\text{NO}}_3^{-}$ on both sides of the vacuolar membrane) to allow us to compare the Nernst equilibrium potential for ${\text{NO}}_3^{-}$ (E_Nernst^NO3) and the measured reversal potential (E_rev) (De Angeli et al., 2006). Third, to test the coupling between ${\text{NO}}_3^{-}$ and H⁺ transport, we shifted the cytosolic pH from 7 to 9 in the presence of ${\text{NO}}_3^{-}$ at the cytosolic side to quantify the change in E_rev. Finally, we exposed each vacuole to the initial bi-ionic conditions to ensure that it was not damaged by the treatments.

Figure 1.

CLCa_E203A overexpression restores tonoplast anion currents but alters the pH dependency of the clca-2 mutant. A, Steady-state current density (I) from Ws-2, clca-2, clca-2/35S:CLCa_E203A L3, and clca-2/35S:CLCa vacuoles under standard conditions in medium containing 20-mM Cl⁻ pH7 (filled rhombus/return filled circle), 4.2-mM ${\text{NO}}_3^{-}$ pH7 (filled square) and 4.2-mM NO–pH 9 (filled triangle). I (pAmper/pFarad) was plotted against the applied membrane potential V (mVolt). Representative whole-vacuole currents from each genotype under standard conditions are shown in the small figures (upper left side of each graph). B, The reversal potentials (E_rev) of the four genotypes were recorded under all measured conditions, revealing elevated E_rev in clca-2/35S:CLCa_E203A L3 vacuoles compared to that of a nitrate channel from Ws-2, confirming that WT CLCa is a ${\text{NO}}_3^{-}$/H⁺ exchanger. Only stable measurements of vacuoles that returned to the initial reversal potentials under the starting conditions (2nd Cl⁻ pH 7) were considered. Data represent means ± sem of n ≥ 5 vacuoles of at least four different plants. One-way analysis of variance (ANOVA) with Bonferroni comparison post-test (P < 0.05) was applied; different letters indicate significant differences inside each genotype.

As previously shown, in vacuoles from clca-2, the current density was much lower than in the wild-type Ws-2 or in clca-2/35S:CLCa, corresponding to a decrease of 66 ± 7% and 89 ± 1%, respectively, at +43 mV under bi-ionic conditions (20 mM Cl⁻ pH 7 at the cytosolic side), (Figure 1A). E_rev in clca-2 was difficult to quantify due to high variance (Supplemental Figure S2B), probably resulting from the very low vacuolar current densities measured in this genotype. Under all conditions, the currents mediated by CLCa_E203A were twice as high as those in clca-2. Notably, in CLCa_E203A vacuoles, no activating kinetics of the ion currents at positive membrane potentials could be observed (Figure 1A), suggesting a link between activation at positive membrane potential and the exchanger mechanism of CLCa. We plotted the measured steady-state current densities (I) against the applied voltage. Under all ionic conditions, a far more negative reversal potential (E_rev) was detected for clca-2/35S:CLCa_E203A vacuoles compared to Ws-2, clca-2/35S:CLCa, and clca-2 vacuoles (Figure 1). While the E_rev of Ws-2 and 35S:CLCa measured when nitrate was in the cytosol confirmed the previously reported 2${\text{NO}}_3^{-}$/1H⁺ transport stoichiometry (De Angeli et al., 2006). In clca-2/35S:CLCa_E203A vacuoles, we observed a reversal potential of −68.5 ± 6.3 mV, which is close to E_Nernst^NO3 = −75 mV. The proximity of the E_rev^E203A and E_Nernst^NO3 indicates that the coupling of anion and H⁺ transport is dramatically affected in CLCa_E203A.

In the next step, the change in pH from 7 to 9 at the cytosolic side of the vacuolar membrane confirmed the disruption of the H⁺ coupling in CLCa_E203A. The cytosolic pH changes significantly modified the measured reversal potentials in Ws-2 (E_rev^pH7 = −27.2 ± 4. mV and E_rev^pH9 = −3.7 ± 10.0) and in clca-2/35S:CLCa (E_rev^pH7 = −23.7 ± 2.0 mV and E_rev^pH9 = −3.4 ± 2.2 mV). Notably, the ΔE_rev values observed in Ws-2 (ΔE_rev = +23.5 ± 6.7 mV) and clca-2/35S:CLCa (ΔE_rev = +20.2 ± 2.7 mV) are close to the expected shift for a 1H⁺/2${\text{NO}}_3^{-}$ antiporter. By contrast, in CLCa_E203A vacuoles, the E_rev was not significantly affected by the shift from pH 7 to 9 at the cytosolic side of the vacuolar membrane (E_rev^pH7 = −68.5 ± 6.3 mV and E_rev^pH9 = −61.6 ± 5.7 mV), confirming the absence of H⁺ coupling in CLCa_E203A mutants (Figure 1B). These data demonstrate that the expression of 35S:CLCa_E203A in the clca-2 mutant did not restore 1H⁺/2${\text{NO}}_3^{-}$ antiporter activity in the vacuolar membrane. Furthermore, we observed a higher current density in clca-2/35S:CLCa_E203A compared to clca-2. Therefore, these data indicate that clca-2/35S:CLCa_E203A plants express a passive ${\text{NO}}_3^{-}$ selective transport system in the vacuolar membrane that is absent in clca-2 and distinct from the 1H⁺/2${\text{NO}}_3^{-}$ antiporter activity detected in the other genotypes.

Expression of CLCa_E203A does not restore plant growth in the clca mutant

Nitrate has been known for decades to be a crucial nutrient for plant growth, notably due to its involvement in nitrogen metabolism (Brouwer, 1962; Crawford, 1995; Chen et al., 2004). We therefore analyzed the consequences of introducing the CLCa_E203A mutation on plant growth. After 6 weeks of growth on 4.25 mM ${\text{NO}}_3^{-}$ under short-day conditions, the fresh weights of clca-2 shoots decreased by 30 ± 5% compared to Ws-2 plants (Figure 2B). The introduction of CLCa restored the wild-type phenotype irrespective of whether the endogenous or 35S promoter was used to drive its expression (Figure 2; Supplemental Figure S3A). Surprisingly, not only did the expression of CLCa_E203A fail to rescue the clca-2 phenotype, but the shoot and root fresh weights of clca-2/35S: CLCa_E203A plants were also further reduced by 26 ± 5% and 29 ± 7%, respectively, compared to clca-2 (Figure 2B). The shoot-to-root fresh weight ratio was not affected in any of the phenotypes, indicating that the plants were not nutrient-starved (Lawlor et al., 2001; Castaings et al., 2009). Expressing CLCa_E203A in clca-2 under the control of the endogenous promoter did not rescue plant shoot fresh weight either (Supplemental Figure S3A). However, only one of the two clca-2/pCLCa:CLCa_E203A lines analyzed displayed a statistically significant reduction in plant fresh weight (22 ± 4%) compared to clca-2. In conclusion, CLCa_E203A expression failed to rescue the growth deficiency phenotype of clca-2 under all conditions and even exacerbated it when over-expressed ubiquitously.

Figure 2.

CLCa_E203A does not complement the biomass production deficiency of clca-2. Ws-2, clca-2, clca-2/35S:CLCa_E203A lines 8 and 3 and complemented line clca-2/35S:CLCa plants were grown hydroponically in 4.25 mM ${\text{NO}}_3^{-}$ under short-day conditions. After 4 weeks, photographs were taken (A) and after 6 weeks, shoot and root fresh weights and shoot/root ratio biomasses were measured (B). Data represent the means ± sem of three biological replicates (n = 3–6 plants per replicate). A Shapiro–Wilk normality test followed by a Welch’s t test was applied. Different letters indicate significant difference between genotypes (P < 0.05). Scale bar represents 1 cm.

Water homeostasis is disrupted in plants expressing CLCa_E203A

In order to understand why the E203A form of CLCa leads to a decrease in plant growth when overexpressed, we explored the impact of uncoupling CLCa on plant water homeostasis. Indeed, nitrate is not only an essential nutrient but also a major signaling molecule and an important osmoticum for plant cells (McIntyre, 1997; Wege et al., 2014). CLCa is expressed in both the mesophyll and guard cells where it is involved in building up the osmotic potential required for proper stomatal movement (Wege et al., 2014). We first measured stomatal opening in response to light in plants overexpressing CLCa_E203A (Figure 3A). As shown previously, stomatal opening is impaired in clca-2 (Wege et al., 2014). In plants overexpressing CLCa_E203A, interestingly, we observed two phases: first, stomatal opening followed the same kinetics as in clca-2 and, after 120 min, in the second phase, stomatal opening was significantly reduced in clca-2/35S:CLCa_E203A compared to clca-2. Similar results were obtained for lines harboring the construct pCLCa:CLCa_E203A (Supplemental Figure S4A). Therefore, the exchanger mechanism of CLCa is required for efficient stomatal opening in response to light. We also investigated stomatal closure induced by ABA in epidermis peels. As expected, stomata from clca-2 responded very weakly to this phytohormone (Wege et al., 2014). In clca-2/35S:CLCa_E203A plants, ABA-induced stomatal closure was reduced to a similar extent as in clca-2 (Figure 3B; Supplemental Figure S4A). Thus, these results show that the uncoupled CLCa responds very weakly to ABA, which affects both stomatal opening and closure. This indicates that the exchanger mechanism is essential for the control of the ionic and (consequently) water fluxes through the vacuolar membrane, which are necessary for the correct functioning of stomata.

Figure 3.

CLCa_E203A plants are affected in stomatal movement. Kinetics of stomatal opening in response to light (A), and the effect of ABA on stomatal closure (B). Experiments were performed on isolated epidermal peels of 5-week-old plants grown for 5 weeks in soil under short-day conditions. Epidermal peels were incubated in KCl buffer for 1 h in the dark before being transferred to the light and incubated for 4.5 h, followed by a 50 μM ABA treatment for 3 h. Data represent the means ± sem of three biological replicates (n = 85–150 per replicate). One-way ANOVA with Bonferroni comparison post-test (P < 0.05); different letters indicate significant difference.

To further analyze the consequences of the mutation in CLCa on water content in whole Arabidopsis plants, we grew plants in well-watered soil under short-day conditions. The dry weight and water content were significantly lower in clca-2 compared to Ws-2 (Figure 4A). This phenotype was restored by overexpressing CLCa, as previously shown (Wege et al., 2014). However, overexpressing CLCa_E203A in clca-2 did not rescue the dry weight or water content to wild-type levels. Instead, this led to a further reduction in water content compared to clca-2, indicating that the coupling of nitrate and proton transport in CLCa is required for water homeostasis. Expressing CLCa_E203A under the control of its endogenous promoter also failed to rescue the water content of clca-2 to wild-type levels (Supplemental Figure S4B). However, only one line displayed a further decrease in water content compared to clca-2, indicating that the overexpression of CLCa_E203A was responsible for the aggravation of the clca-2 growth phenotype in clca-2/35S:CLCa_E203A.

Figure 4.

A, CLCa_E203A plants contain less water than the wild-type, leading to impaired cell enlargement. Relative water content of 6-week-old plants grown as in Figure 3 expressing CLCa_E203A under the control of the 35S promoter. Three biological replicates were performed (n = 25–30 plants per replicate). Statistical analysis as in Figure 3. B, Distribution of relative cell sizes determined by FACS (Fluorescence-Activated Cell Sorting) of protoplasts generated from enzymatically digested leaves of 5-week-old plants grown as in (A). The data presented are representative of one experiment. C, Mean of the relative cell sizes obtained by FACS for each genotype. Two biological replicates (n = three plants per replicate, protoplasts more than 30,000). Statistical analysis as in Figure 3.

As the importance of water for plant cell growth is well established (Boyer, 1968), we decided to investigate the effect of expressing the uncoupled version of CLCa on cell size. This parameter was determined by performing flow cytometry on protoplasts produced by enzymatic digestion of leaves from plants overexpressing CLCa_E203A. Chlorophyll detection allowed us to specifically analyze mesophyll cells and measure the distribution of the relative cell sizes for each genotype (Figure 4, B and C). The sizes of mesophyll cells from the clca-2 KO mutant were clearly reduced compared to Ws-2. Cell size was recovered to wild-type levels upon the expression of native CLCa. By contrast, cells from CLCa_E203A plants were even smaller than those from clca-2 by up to 9.8 ± 3.7% (Figure 4C). The decreased water content observed in plants affected in the gating glutamate of CLCa corresponds to a decrease in relative cell size, which could account for the lower fresh weight of those plants.

Uncoupling ${\text{NO}}_3^{-}$ and H⁺ transport in CLCa modifies nitrate storage and remobilization kinetics

As CLCa was previously characterized for its function in nitrate storage (De Angeli et al., 2006), we analyzed nitrate accumulation in plants expressing CLCa_E203A under the control of the 35S promoter or the endogenous promoter. In agreement with previous findings (Geelen et al., 2000; Monachello et al., 2009), we observed a 37 ± 4% and 30 ± 4% decrease in nitrate content in clca-2 shoots and roots, respectively, compared to Ws-2 (Figure 5A; Supplemental Figure S3C). Strikingly, CLCa_E203A overexpression in the clca-2 background induced a further decrease in nitrate content in shoots (by 52 ± 4%) compared to clca-2, corresponding to a decrease of 70 ± 3% compared to Ws-2. The nitrate content of clca-2/35S:CLCa_E203A roots was similar to that of clca-2. Expressing CLCa_E203A under the control of its own promoter did not lead to a further reduction in nitrate content compared to clca-2 (Supplemental Figure S3C).

Figure 5.

CLCa_E203A expression pattern indicates a decrease in endogenous nitrate but an increase in malate concentration. Endogenous nitrate contents (A) in shoots (left) and roots (right), inorganic anion (B), potassium (C), and malate (D) concentrations in the shoots of Ws-2, clca-2, clca-2/35S:CLCa_E203A, and clca-2/35S:CLCa plants grown hydroponically as described in the legend of Figure 2. Data represent the means ± sem of two experiments (n = 2–9 plants per experiment). Statistical analysis as in Figure 3.

As CLCa can still transport chloride but with lower selectivity compared to nitrate (De Angeli et al., 2006), we measured the content of this anion (Figure 5B). In parallel, we analyzed the concentrations of other major anions and potassium, which are not transported by CLCa but could be affected by the under-accumulation of nitrate (Figure 5, B–D). We found similar levels of these ions in the different genotypes. Nevertheless, clca-2 displayed an increase in malate content, as previously shown (Geelen et al., 2000). This increase was enhanced in clca-2/35S:CLCa_E203A lines. Altogether, these results indicate that CLCa_E203A was not able to restore wild-type levels of nitrate in clca-2 and that uncoupling nitrate and proton transport in CLCa strongly alters nitrate storage in vacuoles.

To better understand the phenotypes of the transgenic lines, we measured the kinetics of nitrate accumulation and remobilization in response to nitrate availability, which mainly reflects the fluxes through the vacuolar membrane (Miller and Smith, 2008; Huang et al., 2012). In these experiments, we decided to focus only on plants overexpressing CLCa_E203A whose nitrate contents were particularly low compared to Ws-2 and clca-2 but whose vacuolar anion currents driven by CLCa were nearly as high as in Ws-2. First, we analyzed the dynamics of nitrate storage in plants expressing CLCa_E203A subjected to nitrate depletion. Plants were grown for 5 weeks under hydroponic conditions in complete Hoagland medium (4.25 mM ${\text{NO}}_3^{-}$) and then exposed to nitrogen starvation for 120 h. The differences in nitrate content in the various lines at the beginning of the experiment corresponded to those observed in our previous tests (Figures 5, A and 6, A). In all genotypes, during the first 72 h of starvation, the kinetics of remobilization were similar in the roots and aerial parts of the plant, apart from Ws-2 roots: all plants lost approximately 0.25 nmol of nitrate per mg of fresh weight per hour (Figure 6A). This led to the complete depletion of nitrate in the roots of clca-2 and clca-2/35S:CLCa_E203A plants. Between 72 and 120 h, the rates of nitrate remobilization in shoots increased, leading to the complete depletion of nitrate in clca-2/35S:CLCa_E203A plants. As a control, we measured the chloride contents in the same plants in parallel (Supplemental Figure S5A). Nitrate starvation led to an increase in Cl⁻ content in the different genotypes and the overaccumulation of Cl⁻ in roots of clca-2/35S:CLCa_E203A compared to Ws-2 and clca-2. These results indicate (1) the plants adjust to the deficiency of negative charges linked to the absence of nitrate by stimulating the absorption of chloride and (2) the net rate of nitrate remobilization is not affected by the lack of CLCa or the presence of CLCa_E203A on the vacuolar membrane. The time it took to reach complete depletion is essentially related to the level of nitrate stored at the beginning of the experiment in the different genotypes and organs.

Figure 6.

clca-2/35S:CLCa_E203A plants exhibit a slower rate of nitrate storage and no change in nitrate remobilization in response to nitrate supply in the medium compared to wild-type. A, Plants were cultivated under hydroponic conditions for 5 weeks as described in Figure 2. Nitrogen was then removed from the medium, and the plants were incubated for 120 h. Nitrate content was determined after 0, 72 h, and 120 h of starvation. B, 5-week-old plants were subjected to 10 days of nitrogen starvation, and 4.25 mM nitrate was supplied again; the nitrate content was determined after 0, 72 h, and 120 h. Nitrate concentration was quantified in shoots (left) and roots (right) separately. In both experiments, data represent the means ± sem of three biological experiments (n = 4–6 plants per replicate). Statistical analysis as in Figure 3. Dotted circles indicate genotypes for which no significant differences were observed compared to other lines. ns, not significant.

To investigate the kinetics of nitrate accumulation in the vacuole, we subjected the plants to nitrogen starvation for 10 days, leading to nitrate concentrations close to zero in all genotypes. We then resupplied the plants with 4.25 mM nitrate and measured nitrate accumulation (Figure 6B). In all genotypes, nitrate content increased when this anion was added to the medium, whereas chloride concentrations decreased, again showing a negative relationship between the quantities of these two anions in planta (Supplemental Figure S5B). Nevertheless, chloride was slightly over-accumulated after 120 h only in shoots (by 23.5 ± 1.0%) in clca-2/35S:CLCa_E203A plants compared to Ws-2 and clca-2. In shoots, at the end of the experiment, a significant difference in the rate of nitrate accumulation between the clca-2 and clca-2/35S:CLCa_E203A lines was obvious, with rates of 0.65 nmol ${\text{NO}}_3^{-}$ mg FW⁻¹ h⁻¹ measured for Ws-2 and clca-2/35S:CLCa but only 0.4 and 0.25 ${\text{NO}}_3^{-}$ mg FW⁻¹ h⁻¹ for clca-2 and clca-2/35S:CLCa_E203A plants, respectively. These differences led to lower nitrate accumulation in clca-2 and the two transgenic lines (39.1 ± 9.7% and 60.5 ± 8.1%, respectively) compared to the wild-type. In roots, the storage rate decreased by up to 24 ± 4% compared to Ws-2 but was similar to that measured in clca-2. These results indicate that introducing the uncoupled form of CLCa in clca-2 strongly decreased the rate of nitrate accumulation in the vacuole, explaining the differences in nitrate contents in the different lines.

CLCa_E203A enhances nitrate assimilation and NUE

The defect in nitrate storage in the vacuole in plants expressing CLCa_E203A likely disturbs cytosolic nitrate homeostasis and consequently alters nitrate assimilation. To test this hypothesis, we measured the activity of NR, the first enzyme involved in nitrate assimilation localized to the cytosol, in 4-week-old clca-2/35S:CLCa_E203A plants with the lowest rate of nitrate storage (Figure 7A). The analysis was performed three hours after the dark–light transition when NR activity is the highest (Man et al., 1999). NR activity increased by 4-fold in clca-2 and 6.5-fold in clca-2/35S:CLCa_E203A compared to wild-type. Consequently, the total amount of free amino acids was higher (by up to 42 ± 2%) in the two transgenic lines overexpressing CLCa_E203A (Figure 7B). However, the total amount of free amino acids did not differ between Ws-2 and clca-2. Interestingly, asparagine (Asn), serine (Ser), glutamine (Gln), and glycine (Gly) levels were significantly higher in the CLCa_E203A lines than in the wild-type, while the concentrations of the other amino acids did not change, indicating that amino acid distribution was modified in these lines (Figure 7B; Supplemental Figure S6). We wondered whether the increase in free amino acid levels induced by uncoupling nitrate and proton transport in CLCa affects the soluble protein content. No significant difference in soluble protein content was observed between the wild-type, clca-2, and clca-2/35S:CLCa. Interestingly, clca-2/35S:CLCa_E203A plants displayed an increased protein content (25 ± 5%) compared to Ws-2 (Figure 7C). These results suggest that inefficient vacuolar nitrate storage due to CLCa_E203A overexpression leads to increased nitrate assimilation into amino acids and proteins.

Figure 7.

clca-2/35S:CLCa_E203A plants have an increased nitrate assimilation rate at the vegetative stage. Ws-2, clca-2, clca-2/35S:CLCa_E203A line 8 and 3, and clca-2/35S:CLCa plants were grown as described in Figure 2 and analyzed for their NR activity (A), total free amino-acid and individual amino-acid contents (B), and soluble protein content (C). For NR activity, the analysis was performed on four to five plants after 3 h in the light. For amino-acid content, four plants were analyzed; asterisks represent significant differences in absolute amino acid content between clca- 2/35S:CLCa_E203A, and Ws-2, clca-2 and clca-2/35S:CLCa. For soluble protein content, three biological replicates including three plants were performed. Data represent the means ± sd; statistical analysis is the same as in Figure 3.

Based on these findings, we wondered whether nitrogen metabolism is also perturbed by CLCa_E203A overexpression at later developmental stages. We therefore determined the NUE in the five genotypes described above. The plants were labeled with ¹⁵N at the seed-filling stage. At harvest, no difference in total dry weight was observed among the genotypes, except for the transgenic line clca-2/35S:CLCa_E203A L3. Nevertheless, dry weight partitioning between rosettes, stems, and roots was the same in all genotypes (Supplemental Figure S7). These results confirm the notion that the altered fresh weight between wild-type and transgenic plants at the vegetative stage described above is mainly due to a change in water status (Figure 4). We then analyzed nitrogen content to quantify N allocation in the aboveground organs. The KO clca-2 mutant retained 18.3% less N than Ws-2 in rosettes, while its seeds were enriched in N by 5.5% (Figure 8A). N partitioning in rosette leaves was even lower in the two clca-2/35S:CLCa_E203A lines (29.5% and 13.7% compared to Ws-2 and clca-2, respectively), which resulted in much higher N partitioning in seeds compared to Ws-2 and clca-2, leading to a higher N concentration in seeds (Figure 8B).

Figure 8.

The mutation in the gating glutamate in CLCa leads to an increased NUE at the seed-filling stage. Ws-2, clca-2, clca-2/35S:CLCaE203A lines 8 and 3, and clca-2/35S:CLCa plants were grown in sand under short days and transferred to long days 1 week before flower bud emergence. Plants were harvested at maturity. N partitioning in rosette, stem, and seeds (A), seed N concentration (B), NRE (C), the RSA ratio (D), and NUE (E). The results for each genotype are means ± sd. Statistical analysis was performed using ANOVA, and the means were classified using Tukey's range test (P < 0.05); different letters indicate significant differences.

This increased nitrogen concentration in seeds cannot be explained by a difference in N remobilization efficiency (NRE) between source and sink organs. Indeed, the values of this parameter, corresponding to the partitioning of ¹⁵N in seeds at harvest compared to the harvest index (¹⁵NHI/HI; Chardon et al., 2012), did not differ among the five genotypes (Figure 8C). In parallel, we estimated the relative-specific absorption ratio (RSA ratio), corresponding to the ratio between ¹⁵N in seeds at harvest and the N harvest index (¹⁵NHI/NHI), indicating the dilution of ¹⁵N in seeds due to post-flowering N uptake (Chardon et al., 2012). These values were lower in clca-2 and clca-2/35S:CLCa_E203A compared to Ws-2 (Figure 8D). These differences may account for differences in N allocation through the different aerial organs of the plants observed previously. Finally, we estimated NUE for seed production, calculating the ratio between the proportion of nitrogen allocated to seeds and the harvest index (NHI/HI; Marmagne et al., 2020). In Ws-2, the NUE value was 1.21 ± 0.18. In clca-2, it increased to 1.30 ± 0.14 and reached 1.43 ± 0.22 in clca-2/35S:CLCa_E203A plants (Figure 8D). These results indicate that mutating the gating glutamate in CLCa leads to the higher allocation of N uptake to seeds and consequently a better NUE at the reproductive stage.

Discussion

In eukaryotes, the CLC membrane protein family comprises both anion/H⁺ exchangers and anion channels. Despite the different transport modes of members of the CLC family, the 3D structures of the two types of CLCs are surprisingly close (Jentsch and Pusch, 2018). This particular feature is mainly related to the substitution of the “gating glutamate” in CLC channels. The physiological consequences of the mutations in this residue have been studied in live animals (Novarino et al., 2010; Weinert et al., 2020). However, the effect of mutating the gating glutamate of CLC exchangers in plants had been unclear. Here, we used the specific function of CLCa in the vacuolar accumulation of nitrate to investigate the importance of this glutamate residue in plants from the cellular to whole-organism level. We found that converting CLCa from an exchanger to a channel by mutating the “gating glutamate” into an alanine strongly altered the nitrate storage capacity and water homeostasis in Arabidopsis, leading to reduced plant growth. However, plants expressing the mutant version of CLCa presented a notable increase in N assimilation and NUE compared to wild-type plants.

The CLCa_E203A mutation leads to decreased nitrate storage in cells

Our results demonstrate that mutating the glutamate 203 of CLCa on the native vacuolar membrane leads to the partial complementation of the anion current compared to the clca-2 KO mutant (Figure 1). Indeed, CLCa_E203A is able to transport anions, but the currents measured in vacuoles extracted from clca-2/35S:CLCa_E203A plants responded differently to variations in cytosolic pH compared to plants expressing the wild-type form of CLCa. In clca-2/35S:CLCa_E203A vacuoles, the ionic currents displayed a reversal potential close to the Nernst potential for ${\text{NO}}_3^{-}$, confirming that CLCa_E203A mediates passive ion fluxes independent from the pH gradient that exists across the tonoplast. These results confirm the data obtained in a previous work performed in Xenopus oocytes (Bergsdorf et al., 2009). Based on these findings and the seven-fold higher selectivity of CLCa for nitrate than for chloride (De Angeli et al., 2006; Wege et al., 2010), we expected that the clca-2/35S:CLCa_E203A lines would be less efficient in accumulating ${\text{NO}}_3^{-}$ in the vacuole. A passive ion transport system in the tonoplast would drive vacuolar nitrate accumulation at a rate 10–15 times lower than an exchanger (Cookson et al., 2005; De Angeli et al., 2006). In line with this prediction, the kinetic measurements performed in planta to analyze nitrate storage and remobilization show a strong decrease in nitrate storage rates in the shoot of clca-2/35S:CLCa_E203A compared to Ws-2 and clca-2 (Figures 5, A and 6). Interestingly, in these experiments, we observed an inverse relation between the accumulation of chloride and nitrate: the plants likely accumulate chloride to compensate for the amount of negative charges inside the cells and to maintain the electrochemical potential gradients through the membranes when nitrate is scarce (Supplemental Figure S5). These results confirm the notion that CLCa_E203A mediates passive nitrate fluxes across vacuolar membranes, whereas the exchanger activity is not required for the efficient accumulation of chloride.

The coupling of proton and anion transport by CLCa is crucial for maintaining water content and ensuring the function of nitrate as an osmoticum

Guard cells are widely used as a model to study the molecular mechanisms involved in the adjustment of cell turgor. Both clca-2 and clca-2/35S:CLCa_E203A are impaired in stomatal opening in response to light due to the under-accumulation of anions in the vacuoles (Figure 3). This finding confirms our previous conclusions on the importance of CLCa in controlling osmotic pressure (Wege et al., 2014). Additionally, in comparing wild-type, clca-2 and clca-2/35S:CLCa_E203A plants, we observed a close relation between shoot water and nitrate contents (Figures 4, A and 5, A), both of which are reduced in clca mutants, indicating the importance of CLCa in nitrate and water homeostasis. Furthermore, the similar levels of potassium and other major inorganic anions, that is, chloride, phosphate, and sulfate, between the genotypes (Figure 5, B and C) confirm the function of nitrate as an osmoticum (McIntyre, 1997). Our results corroborate previous findings (Cardenas-Navarro et al., 1999). More recently, using different mutants of nitrate transporters in Arabidopsis, the nitrate content in shoots was shown to be associated with the water transport capacity of roots (Li et al., 2016). This could also be the case for the different genotypes examined in the current study, especially since CLCa is expressed in mesophyll and guard cells (Geelen et al., 2000; Wege et al., 2014).

In parallel, the characterization of clca mutants revealed that CLCa and its 203rd glutamate residue are essential to sustain plant fresh weight (Figure 2). Several hypotheses can be proposed to explain this result. First, an altered response of the different transgenic plants to ABA, the hormone involved in water homeostasis, may inhibit plant growth. We showed that the stomata of clca-2 and clca-2/35S:CLCa_E203A plants respond very weakly to ABA (Figure 3B), which indicates that the sensitivity to ABA is modified in these plants. However, this hypothesis by itself cannot explain the difference observed in cell size and water content between clca-2 and clca-2/35S:CLCa_E203A lines, as the defects in stomatal movement, are similar in these genotypes. Second, the plants may be disturbed in cytosolic chloride homeostasis, as CLCa is able to transport chloride, albeit with low affinity compared to nitrate (De Angeli et al., 2006; Wege et al., 2010). The kinetic experiments showed that chloride content did not decrease as much in the clca-2/35S:CLCa_E203A lines as in the other genotypes when nitrate was added to the growth medium (Supplemental Figure S5B). Nevertheless, the measured concentrations are below the toxic values and could only partially account for the observed growth phenotype (Jossier et al., 2010). Third, the decrease in stomatal aperture may lead to a reduction in gas exchange with the atmosphere and consequently to an inhibited photosynthetic rate (Figure 3). In mammals, CLC exchangers are thought to work in tandem with vacuolar-type adenosine triphosphatase to maintain intra-compartment pH levels (Satoh et al., 2017). A disruption of pH homeostasis in the different clca-2 lines could also explain the difference in plant fresh weight (Krebs et al., 2010; Demes et al., 2020). Finally, the simplest hypothesis is that the decreased vacuolar ${\text{NO}}_3^{-}$ storage in these genotypes underlies a reduction in cell water potential (Figure 4). Indeed, during root growth, the vacuolar osmotic potential is important for maintaining turgor pressure and for driving cell elongation (Dünser et al., 2019; Kaiser and Scheuring, 2020). Perhaps a similar mechanism operates in mesophyll cells: the under-accumulation of nitrate could lead to reduced cell expansion, which would in turn limit plant growth. Altogether, these results demonstrate the crucial role of a nitrate/proton exchanger on the vacuolar membrane in maintaining water homeostasis and cell expansion in Arabidopsis.

The ${\text{NO}}_3^{-}$/H⁺ exchanger activity of CLCa is essential for regulating nitrate assimilation and therefore NUE

Most of the nitrate in leaves is stored in the vacuoles of mesophyll cells (Martinoia et al., 1981; Miller and Smith, 2008). The decrease in nitrate levels in rosette leaves observed in clca-2/35S:CLCa_E203A plants is most likely due to a reduction in vacuolar nitrate storage. This defect likely perturbs cytosolic nitrate homeostasis, resulting in an increase in NR activity, which would drive increased amino acid and protein synthesis in these lines compared to Ws-2 and clca-2 (Figure 7). These results also confirm the notion that the increase in intracellular nitrate concentration enhances NR activity (Aslam et al., 1987). However, the absence of CLCa in the KO mutant did not lead to increased amino acid and protein accumulation as in the clca-2/35S:CLCa_E203A lines, whereas cytosolic nitrate homeostasis is also perturbed in clca-2 (Monachello et al., 2009). This difference might be explained by the fact that CLCa_E103A expression is driven by the 35S promoter and is likely active in cells of these transgenic lines which is not normally expressed in wild-type plants.

Among the amino acids that overaccumulated in the clca-2/35S:CLCa_E203A transgenic lines (Figure 7B), asparagine and glutamine are preferentially transported through the plant (Havé et al., 2017). Serine and glycine, which also accumulated in the overexpressors, may reflect an increase in photorespiration, the pathway that supplies reductants (such as NADPH) required for nitrate assimilation in C3 plants (Migge et al., 2000; Oliveira et al., 2002; Bloom, 2015). An analysis of the activity of this metabolic pathway will be needed to confirm this hypothesis. In parallel, the clca-2/35S:CLCa_E203A lines accumulated four times more malate than the wild-type (Figure 5D). This increase is not trivial, as malate is a trivalent anion that could compensate for the depletion of negative charges in the vacuolar lumen when the nitrate concentration is reduced. However, malate is also a substrate of the photorespiratory pathway that produces reductants. Furthermore, NR activity requires two protons to reduce one molecule of nitrate into nitrite (Feng et al., 2020). Malate synthesis could then be stimulated to compensate for the alkalization due to increased nitrate assimilation (Bloom, 2015; Eisenhut et al., 2019; Feng et al., 2020).

At the reproductive stage, clca-2 and, to a greater extent clca-2/35S:CLCa_E203A plants showed a different allocation of nitrogen in plant organs than the wild-type, resulting in a higher NUE (Figure 8). These results reflect the enhanced ability of seeds to store N independently of the ability of the plant to produce seeds, pointing to variation in N fluxes during the reproductive phase. CLCa is expressed in roots, rosette leaves, and siliques, but not in seeds (Geelen et al., 2000; David et al., 2014). The large increase in N allocation to seeds in clca-2/35S:CLCa_E203A compared Ws-2 and clca-2 probably results from an indirect effect of defective CLCa in the rosette and stem compartments (stem inflorescences + silique envelopes). Surprisingly, the change in NUE was not due to an increase in N remobilization under this growth condition, as NRE values were similar between the various lines. In contrast, the RSA ratio was significantly reduced in lines in the clca-2 background, indicating higher N uptake after flowering. We previously showed that nitrate influx in roots is reduced in clca KO mutants, but these measurements were performed at the vegetative stage (Monachello et al., 2009). However, more recent work suggested that vacuolar nitrate transporters such as CLCs drive an increase in root N uptake and/or higher root/shoot translocation at later stages of plant development (He et al., 2017; Li et al., 2020), which may explain the low RSA ratios observed in clca-2 lines in the current study. The difference in NUE observed between clca-2 and clca-2/35S:CLCa_E203A lines could be due to a lower nitrate storage capacity in both the rosette and reproductive organs in CLCa_E203A overexpressors. This finding illustrates the importance of nitrogen storage in leaves, stems, inflorescences, and siliques for nitrate uptake by roots and nitrogen allocation in plant organs during seed filling. Nitrate uptake relies on ${\text{NO}}_3^{-}$/H⁺ symporters. The changes in cytosolic nitrate concentration, cytosolic pH, and nitrate assimilation linked to the absence of CLCa or the presence of the uncoupled form of CLCa could modify the activities of these plasma membrane transporters (Filleur and Daniel-Vedele, 1999; Feng et al., 2020). Altogether, this finding highlights the importance of the proton antiport activity of CLCa for regulating nitrate assimilation and consequently NUE.

Based on peptide sequence analysis of the closest homologs of CLCa from algae, lycophytes, bryophytes, and spermaphytes, each species has conserved at least one CLC with the gating glutamate residue (Supplemental Figure S8). This finding points to the strong importance of this residue in the green lineage. Our study on the physiological consequences of the mutation in the gating glutamate of CLCa provides insights into the selective pressure underlying the conservation of exchanger rather than channel activity for this protein. Although this mutation leads to a higher plant nutritional value and better NUE, it also induces a decrease in plant growth due to disrupted water homeostasis, which is expected to severely impair plant fitness. The conservation of the exchange mechanism of CLCa is likely to be associated with the maintenance of water homeostasis irrespective of external nitrogen fluctuations. A previous study showed that a decrease in the vacuolar sequestration of nitrate in roots induces higher nitrate translocation to the shoot, greater nitrate assimilation, and higher biomass (Han et al., 2016). Therefore, perhaps the root-specific expression of CLCa_E203A would provide plants with high protein levels and NUE, but without the disrupted growth likely caused by the expression of CLCa in mesophyll and guard cells. Such analysis would likely provide clues for generating plants with higher NUE without disturbing water homeostasis.

Materials and methods

Plant material

Experiments were performed on A. thaliana (ecotype Wassilewskija [Ws-2]) wild-type plants and the transfer DNA insertion mutant clca-2 (De Angeli et al., 2006). The clca-2/35S:CLCa complemented line was produced in a previous study (Wege et al., 2010). The CLCa_E203A point mutation was introduced into CLCa cDNA using a QuikChange II XL Site-Directed Mutagenesis Kit (Stratagene). The resulting product was introduced into Gateway vector pH2GW7.0 (Karimi et al., 2002) under the control of the 35S promoter or Gateway vector pMDC43 (Curtis and Grossniklaus, 2003), allowing the fusion of GFP at the N-terminal part of CLCa. To generate the clca-2/pCLCa:CLCa and clca-2/pCLCa:CLCa_E203A lines, a 1.9-kb fragment of the CLCa promoter was produced by polymerase chain reaction (PCR) amplification of genomic DNA ([Ws-2] accession) using the primer pair: 5′-NNNNNCCCGGGGGTTTTGCCACTCATACTTT-3′ (Forward) and 5′-NNNNNACTAGTTGGGTGGATGGGTACCATAT-3′ (Reverse). The PCR fragment was cloned into pH2GW7.0 between the SmaI and SpeI restriction sites upstream of the CLCa or CLCa_E203A cDNA sequence. These constructs were used to transform transfer DNA KO plants for CLCa (clca-2) by the floral dip method (Clough and Bent, 1998). The seeds were selected on hygromycin B (20 µg.mL⁻¹), and two T3 homozygous lines were chosen.

Plant growth conditions

All experiments were performed on plants grown under short-day conditions (8-h light, 16-h dark) at 22°C, 60% relative humidity, and 75-µE light intensity (Neon light OSRAM L58W/77). Plants used to measure water and potassium contents were grown for 5 to 7 weeks in Jiffy peat pellets. To measure fresh weight and anion, amino acid, and protein contents, plants were grown hydroponically for 4 to 5 weeks. Seeds were sterilized and sown on seed-holders (Araponics, Liège, Belgium) filled with half-strength MS medium containing 0.60% Phytoagar. The boxes were filled with MilliQ water, incubated at 4°C for 4 days for seed stratification, and transferred to the culture room. Once roots had emerged, the medium was replaced by a modified Hoagland nutrient solution (1.5 mM Ca(NO₃)₂, 1.25 mM KNO₃, 0.75 mM MgSO₄, 0.28 mM KH₂PO₄, micronutrients [50 µM KCl, 25 µM H₃BO₃, 1 µM ZnSO₄, 0.5 µM CuSO₄, 0.1 µM Na₂MoO₄, 5 µM MnSO₄, 20 µM chelated iron Fe-HBED], and 2 mM 2-(N-morpholino)ethanesulfonic acid [MES]; pH 5.7 adjusted with KOH). The nutrient solution was replaced twice a week. For nitrate starvation experiments, the roots of 5-week-old plants grown in a hydroponic system were rinsed twice with nitrate starvation medium (Ca(NO₃)₂ replaced by 1.5 mM CaSO₄ and KNO₃ replaced by 1.25 mM KCl), and the plants were cultured in nitrate starvation medium for 120 h. For the nitrate storage experiment, 4-week-old plants were treated with nitrate starvation for 10 days. The nitrate starvation medium was then replaced by a complete Hoagland nutrient solution, and the plants were incubated for 120 h. For all of these experiments, six plants per genotype were harvested for each time point, and rosettes and roots were harvested separately. These experiments were performed three times.

To measure NUE at the reproductive stage, seeds were stratified in tubes containing water in a cold room for 2 days at 4°C in the dark. After stratification, the seeds were directly sown on sand and watered with 10-mM nitrate solution. Plants were grown in a growth chamber under short-day conditions (8-h/16-h day/night photoperiod) for 7 weeks and transferred to long-day conditions (12-h/12-h day/night photoperiod) until final harvest. The composition of the nutrient solution is described in Chardon et al. (2010). Six to nine plants per genotype were harvested. The experiment was performed twice.

¹⁵N labeling and determination of N partitioning, N remobilization, RSA, and NUE

One week before transfer, when the plants were in the exponential vegetative growth phase, the plants were watered with 10 mM ¹⁵${\text{NO}}_3^{-}$ 10% enrichment solution. To analyze unlabeled samples, a few ¹⁵${\text{NO}}_3^{-}$-free plants were harvested in order to determine the natural abundance of ¹⁵N. After 2 days, the sand was rinsed twice in deionized water baths. At the end of the cycle, when all seeds were mature and the rosette dry, plants were harvested. The samples were separated as (1) rosette (rosette leaves), (2) stem (inflorescence stem + cauline leaves + empty dry siliques), and (3) seeds (total seeds) and their dry weights were determined. Subsamples of 1,000–2,000 μg were carefully weighed in tin capsules to determine the total N percentage (N% as mg (100 mg DW)⁻¹) and the ¹⁵N abundance using a FLASH 2000 Organic Elemental Analyzer (Thermo Fisher Scientific) coupled to a Delta V Advantage isotope ratio mass spectrometer (Thermo Fisher Scientific). The ¹⁵N abundance in each sample was measured as atom percent and defined as A% = 100 × (¹⁵N)/(¹⁵N+ ¹⁴N). In the unlabeled plant controls, A% control was 0.3660. The ¹⁵N enrichment (E%) of the plant material was then calculated as (A%sample – A%control). The absolute quantity of N and ¹⁵N contained in the sample was calculated as QtyN = DW×N% and Qty¹⁵N = DW × E% × N%, respectively. The parameters used to evaluate HI, NUE, N remobilization, and its components were defined as follows:

$$\text{HI}={\text{DW}}_{\text{seeds}}/\left({\text{DW}}_{\text{rosette}}+{\text{DW}}_{\text{Stem}}+{\text{DW}}_{\text{seeds}}\right),$$

$$\mathrm{N} \text{allocation in rosette}={ \text{QtyN}}_{\text{rosette}}/\left({\text{QtyN}}_{\text{rosette}}+{\text{QtyN}}_{\text{stem}}+{\text{QtyN}}_{\text{seeds}}\right),$$

$$\mathrm{N} \text{allocation in stem}={ \text{QtyN}}_{\text{stem}}/\left({\text{QtyN}}_{\text{rosette}}+{\text{QtyN}}_{\text{stem}}+{\text{QtyN}}_{\text{seeds}}\right),$$

$$\mathrm{N} \text{allocation in seeds} \left(\text{NHI}\right)={ \text{QtyN}}_{\text{seeds}}/\left({\text{QtyN}}_{\text{rosette}}+{\text{QtyN}}_{\text{stem}}+{\text{QtyN}}_{\text{seeds}}\right),$$

$$\text{NRE}{=}^{15}\text{NHI}/\text{HI},$$

$$\text{RSA}{=}^{15}\text{NHI}/\text{NHI}$$

$$\text{NUE}=\text{NHI}/\text{HI}$$

Reverse Transcription-quantitative PCR (RT-qPCR) analysis

Total RNA was extracted from 4-week-old plants using an RNeasy kit (Qiagen, Germany), and 2 µg of RNA was reverse-transcribed using SuperScript IV Reverse Transcriptase according to the manufacturer’s instructions (Thermo Fisher Scientific). Real-time PCR was performed on complementary DNAs in a final volume of 10 µL using SYBR (Synergy Brands, Inc) Green I master mix (Roche Life Science) and specific primers: for CLCa, 5′-ATCAAATGGAGATGGCTTCG-3′ (Forward) and 5′-CCTCAAGAGCGAAAAGTACTC-3′ (Reverse); and for the ACTIN2 reference gene, 5′-GGTAACATTGTGCTCAGTGGTGG-3′ (Forward) and 5′-AACGACCTTAATCTTCATGCT-3′ (Reverse). The reactions were performed in a LightCycler 96 real-time PCR system (Roche Life Science). Samples were subjected to ten minutes of pre-incubation at 95°C, followed by 45 amplification cycles of 15 s at 95°C, 15 s at 60°C, and 15 s at 72°C. High-resolution melting was performed to assess amplification specificity, and several cDNA dilutions were tested to calculate primer efficiency. The results were analyzed using LightCycler Software (Roche Life Science) and normalized to ACTIN2 gene expression.

Confocal microscopy

The localization of CLCa_E203A was examined under a Leica TCS SP8 confocal microscope using a fusion protein containing GFP at the N-terminal part of CLCa. The GFP was excited at 488 nm, and its fluorescence emission signal was analyzed between 500 and 525 nm.

Electrophysiological experiments

Vacuoles for electrophysiological experiments were extracted from A. thaliana mesophyll protoplasts as described before (Song et al., 2003). Patch clamp recordings were performed in the whole-vacuole configuration and recorded with an EPC-10 USB patch clamp amplifier (HEKA, Lambrecht-Pfalz, Germany). The recordings were acquired and controlled with PatchMaster software (HEKA, Lambrecht-Pfalz, Germany). Currents were induced by five-second pulses from −97 to +63 mV in 20 mV increments, and the potentials were corrected by the liquid junction potential (Neher, 1992). Standard solutions were as follows: (vacuolar) 200 mM Bis-Tris-Propane (BTP) ${\text{NO}}_3^{-}$, 2 mM MgCl₂, 0.1 mM CaCl₂, 10 mM MES pH 5.5; (cytosolic) 20 mM BTP Cl⁻, 10 mM MES pH 7, 0.1 mM CaCl₂, 2 mM MgCl₂; pH 7. Cytosolic ${\text{NO}}_3^{-}$ solutions containing 0.1 mM Ca(NO₃)₂, 2 mM Mg(NO₃)₂, and 10 mM BTP were adjusted to pH 7 or pH 9 with MES. The osmolarity of the solutions was adjusted to π = 600 mOsm with sorbitol. Only measurements of stable vacuoles that returned to the initial reversal potentials under the starting conditions were considered.

Measuring plant compound contents and NR activity

To measure nitrate and chloride contents, shoots and roots of 5-week-old plants were harvested separately, weighed, and fast frozen in liquid nitrogen. The plant material was ground, homogenized in 1 mL (shoot) or 500 µL (root) of MilliQ water, and exposed to three successive freeze–thaw cycles. After the last thawing, the samples were centrifuged for 10 min at full speed (Sorvall Legend Micro21) to pellet the cell debris and recover the supernatant to be used for nitrate and chloride colorimetric assays (Miranda et al., 2001). To measure anion content, shoot samples were subjected to high performance liquid chomatography (HPLC) analysis (ICS5000, ThermoFisher) or used to measure malate content using a colorimetric assay kit (BioVision). To analyze potassium content, shoots were harvested and dried at 60°C for 3 days. The dried samples were digested in 2 mL of 70% nitric acid in a DigiBlock ED36 (LabTech) at 80°C for 1 h, 100°C for 1 h, and then 120°C for 2 h. After diluting in ultra-pure water, the potassium content was determined by atomic absorption spectrometry using an AA240FS flame spectrometer (Agilent Technologies).

NR activity was measured as described by Kim and Seo (2018). To quantify amino acids, the shoots of plants were rapidly frozen in liquid nitrogen and lyophilized overnight. The dried material was weighed to equalize the sample sizes and finely ground in liquid nitrogen with a pestle and mortar. Polar metabolites were extracted in 80% methanol, 20% water containing 0.2 mM α-Amino-n-Butyric Acid as an internal standard. The samples were centrifuged at 1,400 rpm for 5 min, and several aliquots were dried overnight under a vacuum. Prior to HPLC analysis (Waters Alliance instrument with a Waters 2475 multi-wavelength fluorescence detector), the aliquots were resuspended in MilliQ water and filtered into autosampler vials before precolumn derivatization. Standard amino-acid solutions were used to generate calibration curves; a correction was performed using internal standard variation and normalized by dry weight. To measure soluble protein content, 100 mg of each plant was harvested and ground in liquid nitrogen. After adding 350 µL of extraction buffer (50 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid [HEPES]/NaOH pH 7.2, 1.5-mM MgCl₂, 1 mM ethylene glycol-bis(β-aminoethyl ether)-N,N,N′,N′-tetraacetic acid [EGTA] 0.2M, 10% glycerol, 1% Triton, 2 mM phenylmethylsulfonyl fluoride [PMSF], 150 mM NaCl, antiprotease-etheylenediaminetetraacetic acid [EDTA]), the sample was homogenized by vortexing. The samples were incubated under agitation at 20 rpm on a vertical rotator for 30 min at 4°C. After centrifugation, the supernatant was recovered and used to measure total soluble protein content using a standard Bradford assay (Bradford, 1976).

Measuring stomatal dynamics

Stomatal measurements were performed on 5-week-old plants as described in Jossier et al. (2010). Two hours before the beginning of the light period, plants were collected and two leaves per genotype were glued onto coverslips with surgical glue (Hollister Medical Adhesive, Adapt^TM 7730) to peel the epidermis. The cover slides were immediately immersed in MES/KCl buffer (50 mM, pH 6.15 with KOH) and kept in the dark for 1 h. After this dark period, images were acquired for the initial stomatal aperture measurements, and the aperture was monitored after inducing opening by treatment with 75 µE of light for 4.5 h at 22°C. For the stomatal closing experiment, the epidermis samples were then incubated for 3 h in 50-µM ABA, and the aperture area was determined. Images acquisition was performed with a 40× objective on a wide field inverted microscope (DMI600B, Leica, Imagerie Gif, Gif-Sur-Yvette) coupled to a Hamamatsu camera. To capture stomatal images, Z-stacks were acquired to obtain a clear image of all cells. Ostiole (pore) area was measured automatically on different types of z-projections via a procedure we developed with ImageJ software (Schneider et al., 2012; Supplemental Figure S9). Our procedure, implemented in ImageJ, is based on wide-field microscopic images of epidermal peels in which the guard cell walls delimiting the ostiole are amongst the darkest area of the image (low pixel values), while the ostiole aperture is represented by bright (high pixel values) area (see pictures below). Z-stacks composed of 18 planes (voxel dimensions x–y–z, 161–161–691 nm) were acquired. In the first step, minimal intensity z-projections of the stacks were smoothed with a “Gaussian Blur” filter (sigma = 5), and thresholded (Yen method) to generate objects corresponding to the inner cell walls of guard cells. These objects were then size- and shape-filtered with the “Analyze particles” command (size = 20–150 circularity = 0.35–1.00), and fitted with ellipses to generate regions of interest (ROIs) delimiting an inner area of the stomata (in yellow in the figure below). Optional manual inspection and, when necessary, curation of these ROIs allowed for the identification of 100% of the stomata present in each image. Then, to obtain ROIs defining stomatal aperture, this time a maximum intensity z-projection of the stack was thresholded (AutoLocalThreshold method), considering only pixels within the previously defined ellipsoidal regions. Pixels selected by this nested thresholding strategy were again fitted with an ellipse, to generate this time aperture ROIs precisely delimiting stomata openings (in magenta in Supplemental Figure S9). Data on stomata opening were extracted from the geometric properties of these ROIs. The imageJ macro employed and sample images can be obtained from the authors upon request. Measurements were performed on 86–150 stomata per genotype per treatment (two leaves) and were repeated three times.

Measuring plant water content

To measure plant water content, rosettes were harvested and weighed (n = 10 for each genotype per biological replicate, the experiment was repeated three times), dried for 3 days at 65°C, and relative water content calculated as: (FreshWeight–DryWeight)/FreshWeight. Relative water contents were determined in a similar manner during dehydration tests performed on 7-week-old plants under a laminar flow hood as described by Wege et al. (2014).

Measuring cell size

Flow cytometry was used to measure relative cell sizes in leaves. Seven leaves were harvested from 5-week-old plants using three plants per genotype and digested with an enzymatic mixture (1% cellulase R-10, 0.2% Macerozyme R-10, 0.4 M mannitol, 20 mM KCl, 20 mM MES/KOH pH 5.7, 10 mM CaCl₂, 0.1% w/v bovine serum albumine [BSA]) for 3 h. Protoplasts were retrieved by centrifugation at low speed (100 g) for 2 min. Protoplasts were resuspended in a solution of 1 mM CaCl₂, 10 mM MES pH 5.3 (KOH), 594 mOsm with sorbitol and filtered through a 50-µm nylon filter. The protoplasts were analyzed on a MoFlo Astrios cytometer, driven by Summit 6.3 (Beckman–Coulter). Chlorophyll was excited by a 488 nm solid-state laser (150 mW), measuring emission at 664/22 nm. Forward Scatter (FSC, size) and Side Scatter (SSC, granularity) were measured using a 488 nm laser. The first region of interest (gate) was focused on events with highly homogeneous fluorescence of chlorophyll. The mean values of FSC-Area and SSC-Area parameters were then measured using the same gating strategy for each sample. Each histogram represents more than 30,000 protoplasts.

Phylogeny

The protein sequences with homology to AtClCa were retrieved from Phytozome v13 and Plaza 4.0 Dicots using Blast homology searches. They were aligned using Phylogeny (https://www.phylogeny.fr/) using the “one click” workflow. The sequence of the bacterial ClC from E. coli (ClC-ec1) was added as a reference. The alignment used to create the phylogenetic tree is provided as Supplemental Data File 1.

Statistical analysis

Data processing (mean, standard errors), graphs, and one-way analysis of variance were performed using GraphPad-Prism software (version 5.00.288). When the number of samples was low per genotype, a Shapiro–Wilk normality test followed by a Welch’s t test was applied using Microsoft Excel (version 2016). Differences were considered statistically significant when P < 0.05. All the statistical results are summarized in Supplemental Data Set 1.

Accession numbers

Sequence data from this article can be found in the GenBank/EMBL data libraries under accession number At5g40890 (CLCa).

Supplemental data

The following materials are available in the online version of this article:

Supplemental Figure S1 . CLCa expression in CLCa_E203 transgenic lines, and subcellular localization of CLCa_E203A.

Supplemental Figure S2 . Steady-state current density from clca-2/35S/CLCa_E203 L8 and reversal potentials of clca-2.

Supplemental Figure S3 . Physiological consequences of pCLCa:CLCa_E203A expression in clca-2 on plant growth and nitrate content.

Supplemental Figure S4 . Physiological consequences of pCLCa:CLCa_E203A expression in clca-2 on water homeostasis.

Supplemental Figure S5 . Chloride contents of clca-2/35S:CLCa_E203A plants.

Supplemental Figure S6 . Contents of the amino acids not modified in clca-2/35S:CLCa_E203A plants.

Supplemental Figure S7 . Biomass allocation in the aerial organs of the different genotypes.

Supplemental Figure S8 . The gating glutamate is highly conserved in the closest homologs of CLCa.

Supplemental Figure S9 . Nested thresholding approach employed to measure stomata aperture.

Supplemental Data Set 1 . Statistical data.

Supplemental Data File 1 . Alignment used to generate the phylogenetic tree in Supplemental Figure S8.

 

A.D.A., S.T. and S.F. designed the project. J.H., C.L., C.E., and F.A-C. performed the experiments, M.B. conducted the cytometry measurements. M.W.B. developed the macro running under Image J to analyze the ostiole area. J.H., C.L., C.E. and A.D.A. analyzed the data. A.M. and F.C. performed and analyzed the NUE experiment. J.H., C.L. and S.F. wrote the manuscript. All authors revised the article.

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 (https://academic.oup.com/plcell) is: Sophie Filleur (sophie.filleur@i2bc.paris-saclay.fr).