Focus Issue on Calcium Signaling: Recent Advances in Calcium/Calmodulin-Mediated Signaling with an Emphasis on Plant-Microbe Interactions

Calcium/calmodulin-mediated signaling contributes in diverse roles in plant growth, development, and response to environmental stimuli.During calcium (Ca2+) signaling, decoding the stimulus-response coupling involves a set of Ca2+ sensor proteins or Ca2+-binding proteins (DeFalco et al., 2010a; Kudla et al., 2010). These proteins usually possess one or more classical helix-loop-helix elongation factor (EF) hand motifs. Three major types of Ca2+-sensor proteins in plants are calmodulin (CaM)/CaM-like proteins, calcium-dependent protein kinases (CDPKs), and calcineurin B-like proteins. As compared with animals, plant genomes encode more diversified Ca2+ sensors; with the exception of canonic CaM, all other types of Ca2+ sensors (CaM-like proteins, CDPKs, and calcineurin B-like proteins) are plant specific. The large population and unique structural composition of Ca2+-binding proteins and the diversity of the target proteins regulated by the Ca2+ sensors reflect the complexity of Ca2+ signaling, which helps plants adapt to the changing environment. This update will be limited primarily to discussions on CaM and CaM-binding proteins and the recent advances in Ca2+/CaM-mediated signaling.CaM is a conserved Ca2+-binding protein found in all eukaryotes. The discovery of CaM can be traced back to the 1970s. An activator of cyclic nucleotide phosphodiesterase was shown to be involved in the regulation of cAMP concentration, which was stimulated by Ca2+ (Kakiuchi and Yamazaki, 1970; Cheung, 1971). The activator was found to bind Ca2+ and was eventually named “calmodulin,” an abbreviation of Ca2+-modulated protein. Since its discovery over 40 years ago, CaM has been regarded as a model Ca2+-binding protein and has been subjected to intensive studies in biochemistry, cell biology, and molecular biology because of its importance in almost all aspects of cellular regulation (Poovaiah and Reddy, 1987, 1993; Bouche et al., 2005; DeFalco et al., 2010a; Du et al., 2011; Reddy et al., 2011b). Disruption or depletion of the single copy of the CaM gene in yeast (Saccharomyces cerevisiae) results in a recessive lethal mutation (Davis et al., 1986), suggesting that CaM has a critical role in eukaryotic cells.The structure of CaM has been well studied, and the prototype of CaM found in all eukaryotes has 149 amino acids with two globular domains, each containing two EF hands connected by a long flexible helix (Meador et al., 1993; Zhang et al., 1995; Yun et al., 2004; Ishida et al., 2009). As more and more genomes are sequenced, it is becoming clear that CaM belongs to a small gene family in plants. In the model plant Arabidopsis (Arabidopsis thaliana), seven CaM genes encode for four highly conserved isoforms (CaM1/4, CaM2/3/5, CaM6, and CaM7) that differ in only one to five amino acid residues. Loss-of-function mutations of individual CaMs indicate that the different CaMs may have overlapping yet different functions. For example, a loss of function in Arabidopsis AtCaM2 affects pollen germination (Landoni et al., 2010). Phenotypic analysis showed that in normal growth conditions, atcam2-2 plants were indistinguishable from the wild type, while genetic analysis showed a reduced transmission of the atcam2-2 allele through the male gametophyte, and in vitro pollen germination revealed a reduced level of germination in comparison with the wild type. However, the atcam3 knockout mutant showed a clear reduction in thermotolerance after heat treatment at 45°C for 50 min (Zhang et al., 2009). Overexpression of AtCaM3 in either the atcam3 knockout or wild-type background significantly rescued or increased the thermotolerance, respectively. Further analysis of individual CaM mutants under different stress conditions should reveal more on the functional significance of individual CaM genes.     

Calcium/Calmodulin-Dependent Protein Kinase Is Negatively and Positively Regulated by Calcium,Providing a Mechanism for Decoding Calcium Responses during Symbiosis Signaling

The establishment of symbiotic associations in plants requires calcium oscillations that must be decoded to invoke downstream developmental programs. In animal systems, comparable calcium oscillations are decoded by calmodulin (CaM)–dependent protein kinases, but symbiotic signaling involves a calcium/CaM–dependent protein kinase (CCaMK) that is unique to plants. CCaMK differs from the animal CaM kinases by its dual ability to bind free calcium, via calcium binding EF-hand domains on the protein, or to bind calcium complexed with CaM, via a CaM binding domain. In this study, we dissect this dual regulation of CCaMK by calcium. We find that calcium binding to the EF-hand domains promotes autophosphorylation, which negatively regulates CCaMK by stabilizing the inactive state of the protein. By contrast, calcium-dependent CaM binding overrides the effects of autophosphorylation and activates the protein. The differential calcium binding affinities of the EF-hand domains compared with those of CaM suggest that CCaMK is maintained in the inactive state at basal calcium concentrations and is activated via CaM binding during calcium oscillations. This work provides a model for decoding calcium oscillations that uses differential calcium binding affinities to create a robust molecular switch that is responsive to calcium concentrations associated with both the basal state and with oscillations.     

Dynamic Changes in the Distribution of Minerals in Relation to Phytic Acid Accumulation during Rice Seed Development

Phytic acid (inositol hexakisphosphate [InsP₆]) is the storage compound of phosphorus in seeds. As phytic acid binds strongly to metallic cations, it also acts as a storage compound of metals. To understand the mechanisms underlying metal accumulation and localization in relation to phytic acid storage, we applied synchrotron-based x-ray microfluorescence imaging analysis to characterize the simultaneous subcellular distribution of some mineral elements (phosphorus, calcium, potassium, iron, zinc, and copper) in immature and mature rice (Oryza sativa) seeds. This fine-imaging method can reveal whether these elements colocalize. We also determined their accumulation patterns and the changes in phosphate and InsP₆ contents during seed development. While the InsP₆ content in the outer parts of seeds rapidly increased during seed development, the phosphate contents of both the outer and inner parts of seeds remained low. Phosphorus, calcium, potassium, and iron were most abundant in the aleurone layer, and they colocalized throughout seed development. Zinc was broadly distributed from the aleurone layer to the inner endosperm. Copper localized outside the aleurone layer and did not colocalize with phosphorus. From these results, we suggest that phosphorus translocated from source organs was immediately converted to InsP₆ and accumulated in aleurone layer cells and that calcium, potassium, and iron accumulated as phytic acid salt (phytate) in the aleurone layer, whereas zinc bound loosely to InsP₆ and accumulated not only in phytate but also in another storage form. Copper accumulated in the endosperm and may exhibit a storage form other than phytate.The transport of nutrients into developing seeds has received considerable attention. During the grain-filling stage, plants remobilize and transport nutrients distributed throughout the vegetative source organs into seeds. Plant seeds contain large amounts of phosphorus (P) in organic form, which supports growth during the early stages of seedling development. Most of the P in seeds is stored in the form of phytic acid (inositol hexakisphosphate [InsP₆]). Seeds also accumulate mineral nutrients such as potassium (K), magnesium (Mg), calcium (Ca), iron (Fe), zinc (Zn), copper (Cu), and manganese (Mn), which are used in seedling growth. Phytic acid acts as a strong chelator of metal cations and binds them to form phytate, a salt of InsP₆ (Lott et al., 2002; Raboy, 2009). During germination, phytate is decationized and hydrolyzed by phytases, and then inorganic phosphates, inositol, and various minerals are released from the phytate (Loewus and Murthy, 2000). Phytate accumulates within protein bodies, generally of vacuolar origin, in seed storage cells and is usually concentrated in spherical inclusions called globoids. Many studies of the elemental composition of phytate in seeds have been published. Energy-dispersive x-ray microanalyses of many plant species have revealed that, other than P, globoids contain mainly K and Mg as well as low levels of Ca, Mn, Fe, and Zn (Lott, 1984; Lott et al., 1995; Wada and Lott, 1997). This indicates that phytate is a mixed salt of these cations.Whether all storage metal elements can bind equally to InsP₆ is not known, although most elements are thought to exist in seeds in the form of phytate (Raboy, 2009). To form phytate, P and the other elements must be present in the same place. Therefore, determination of the precise locations of P and other elements in seed tissues makes it possible to judge whether an element exists in the form of phytate. Differences in metal distribution with P might suggest a storage form other than phytate. For determining distributions, synchrotron-based x-ray microfluorescence (µ-XRF) imaging utilizing an x-ray microbeam is a powerful tool. The microbeam excites the elements, thereby revealing the details of their spatial distribution. The development of focusing optics for high-energy x-rays using a Kirkpatrick-Baez mirror raises the imaging resolution of elements in µ-XRF analysis. A focal spot size smaller than 1 µm with x-ray energy as high as 100 keV enables detection of the subcellular distribution of elements in plant tissues (Fukuda et al., 2008; Takahashi et al., 2009).Whether there is an order in the affinity of elements for phytic acid in plant cells remains unknown. The stability of InsP₆-metal complexes has been estimated by in vitro titration (Maddaiah et al., 1964; Vohra et al., 1965; Persson et al., 1998). The binding strength of InsP₆ with metal is stronger for Zn and Cu than for Fe, Mn, and Ca. We also do not know if the mineral composition of phytate in seeds is determined by the relative abundance of these elements in the seed or by their biochemical characteristics. As a first step to address these issues, we examined the simultaneous changes in the distribution of P and metal elements during seed development using µ-XRF imaging analysis.Our objective in this study was to observe the dynamic changes in the distribution of some nutritionally important minerals (P, Ca, K, Fe, Zn, and Cu) in relation to the accumulation of phytic acid during rice (Oryza sativa) seed development.     

Focus on Water: Polarity of Water Transport across Epidermal Cell Membranes in Tradescantia virginiana

Using the automated cell pressure probe, small and highly reproducible hydrostatic pressure clamp (PC) and pressure relaxation (PR) tests (typically, applied step change in pressure = 0.02 MPa and overall change in volume = 30 pL, respectively) were applied to individual Tradescantia virginiana epidermal cells to determine both exosmotic and endosmotic hydraulic conductivity (L_pOUT and L_pIN, respectively). Within-cell reproducibility of measured hydraulic parameters depended on the method used, with the PR method giving a lower average coefficient of variation (15.2%, 5.8%, and 19.0% for half-time, cell volume [V_o], and hydraulic conductivity [L_p], respectively) than the PC method (25.4%, 22.0%, and 24.2%, respectively). V_o as determined from PC and PR tests was 1.1 to 2.7 nL and in the range of optically estimated V_o values of 1.5 to 4.9 nL. For the same cell, V_o and L_p estimates were significantly lower (about 15% and 30%, respectively) when determined by PC compared with PR. Both methods, however, showed significantly higher L_pOUT than L_pIN (L_pOUT/L_pIN ≅ 1.20). Because these results were obtained using small and reversible hydrostatically driven flows in the same cell, the 20% outward biased polarity of water transport is most likely not due to artifacts associated with unstirred layers or to direct effects of externally applied osmotica on the membrane, as has been suggested in previous studies. The rapid reversibility of applied flow direction, particularly for the PR method, and the lack of a clear increase in L_pOUT/L_pIN over a wide range of L_p values suggest that the observed polarity is an intrinsic biophysical property of the intact membrane/protein complex.The conductivity of membranes to water (hydraulic conductivity [L_p]) is an important property of the cells of all organisms, and whether plant cell membranes exhibit a polarity in this property has been debated for a number of decades (Dainty and Hope, 1959; Steudle, 1993). Most early evidence for polarity was based on transcellular osmotic experiments using giant algal cells in the Characeae, in which the relative areas of cell membrane exposed to conditions of osmotic inflow (endosmosis) or outflow (exosmosis) could be varied and, hence, L_p for both directions determined (Tazawa and Shimmen, 2001). Interpretation of these experiments is complicated by unstirred layer (USL) effects (Dainty, 1963), but even after accounting for these, it was concluded that inflow L_p (L_pIN) was higher than outflow L_p (L_pOUT) in these cells, with L_pOUT/L_pIN of about 0.65 (Dainty, 1963). When using osmotic driving forces in algal cells, L_pOUT/L_pIN values of between 0.5 and 0.91 have been reported in many studies (Steudle and Zimmermann, 1974; Steudle and Tyerman, 1983; Tazawa et al., 1996), and the same direction of polarity was also reported using osmotic driving forces in whole roots of maize (Zea mays; Steudle et al., 1987). When applying hydrostatic driving forces in algal cells using the pressure probe (Steudle, 1993), which is less influenced by USL effects (Steudle et al., 1980), L_pOUT/L_pIN has been closer to 1 (0.83–1; Steudle and Zimmermann, 1974; Steudle and Tyerman, 1983). However, in higher plant cells, an analysis of the data presented by Steudle et al. (1980, 1982) and Tomos et al. (1981) indicates the opposite polarity, with L_pOUT/L_pIN averaging from 1.2 to 1.4. Moore and Cosgrove (1991) used two contrasting hydrostatic methods to measure L_p in sugarcane (Saccharum spp.) stem cells: (1) the most commonly used pressure relaxation (PR) method, in which cell turgor pressure (P_cell) changes during the measurement, and (2) the more technically demanding pressure clamp (PC) method, in which P_cell is maintained constant. Consistent with other studies in higher plant cells, Moore and Cosgrove (1991) reported average L_pOUT/L_pIN from 1.15 (PC) to 1.65 (PR). Using the PR method in epidermal cells of barley (Hordeum vulgare), Fricke (2000) reported only a modest L_pOUT/L_pIN (based on reported half-time [T_1/2]) of 1.08. In view of the contribution of proteins (e.g. aquaporins) to overall membrane L_p, Tyerman et al. (2002) suggested that polarity may result either from asymmetry in the pores themselves or from an active regulation of the conductive state of the pores in response to the experimental conditions that cause inflow or outflow. Either of these mechanisms may explain the wide range of values reported in the literature for L_pOUT/L_pIN. Cosgrove and Steudle (1981) reported that a substantial (6-fold) and rapid (within 20 s) reduction in L_p could occur in the same cell, and in hindsight, this presumably reflected the influence of aquaporins. Cosgrove and Steudle (1981) did not consider the lower L_p as indicative of the L_p in situ, and Wan et al. (2004) reported that a reduction in L_p was associated with perturbations to P_cell on the order of 0.1 MPa. Hence, if measured membrane L_p itself can exhibit substantial changes over relatively short periods of time in the same cell, then further study of systematic differences between L_pOUT and L_pIN will require a robust hydrostatic methodology (PC or PR) that can reversibly and reproducibly apply small perturbations in pressure (P) to individual cells over short periods of time.For the PR method, a T_1/2 of water exchange is measured by fitting an exponential curve to the observed decay in P_cell over time following a step change in volume, and membrane L_p can be calculated if cell surface area (A), cell volume (V_o), and volumetric elastic modulus (ε) are known (Steudle, 1993). In practice, A and V_o are typically calculated from optical measurements of individual cell dimensions or estimates using average values, and ε is calculated based on V_o and an empirical change in pressure (dP) to change in volume (dV) relation for each cell (Steudle, 1993; Tomos and Leigh, 1999). In the PC method, first developed by Wendler and Zimmermann (1982), V_o (and, given reasonable assumptions about cell geometry, A) is estimated without the need for optical measurements, and L_p can be measured without the need to determine dP/dV or ε. However, this method is technically more demanding because it requires precise P control as well as a continuous record of the volume flow of water across the cell membrane (as measured by changes in the position of the cell solution/oil meniscus within the glass capillary over time) and has rarely been used (Wendler and Zimmermann, 1982, 1985; Cosgrove et al., 1987; Moore and Cosgrove, 1991; Zhang and Tyerman, 1991; Murphy and Smith, 1998). Since volume (V) is continuously changing over time, this approach may also be influenced by the hydraulic conductance of the capillary tip (K_h) used to make the measurements as well as surface tension effects due to the progressive changes in capillary diameter with meniscus position, and these influences have not been quantitatively addressed.Automation of the pressure probe operation, particularly automatic tracking of the meniscus location in the glass microcapillary tip, would address many of the above-mentioned issues, and to date, several attempts have been made to monitor the meniscus location using electrical resistance (Hüsken et al., 1978) or hardware-based image analysis (Cosgrove and Durachko, 1986; Murphy and Smith, 1998). Recently, Wong et al. (2009) redesigned the automated cell pressure probe (ACPP), originally proposed by Cosgrove and Durachko (1986), using a software-based meniscus detection system and a precise pressure control system. In the new ACPP system, both the position of the meniscus and oil pressure (P_oil) are recorded frequently (typically at 10 Hz), and P_oil is controlled with a resolution of ±0.002 MPa. We have combined the ACPP with a new technique to reproducibly fabricate microcapillary tips of known hydraulic properties (Wada et al., 2011) in order to correct for K_h and surface tension effects in both PC and PR estimates of the water relations parameters of Tradescantia virginiana epidermal cells and have determined the relation of L_pOUT to L_pIN in these cells.     

Brassinosteroid Regulates Cell Elongation by Modulating Gibberellin Metabolism in Rice

Brassinosteroid (BR) and gibberellin (GA) are two predominant hormones regulating plant cell elongation. A defect in either of these leads to reduced plant growth and dwarfism. However, their relationship remains unknown in rice (Oryza sativa). Here, we demonstrated that BR regulates cell elongation by modulating GA metabolism in rice. Under physiological conditions, BR promotes GA accumulation by regulating the expression of GA metabolic genes to stimulate cell elongation. BR greatly induces the expression of D18/GA3ox-2, one of the GA biosynthetic genes, leading to increased GA₁ levels, the bioactive GA in rice seedlings. Consequently, both d18 and loss-of-function GA-signaling mutants have decreased BR sensitivity. When excessive active BR is applied, the hormone mostly induces GA inactivation through upregulation of the GA inactivation gene GA2ox-3 and also represses BR biosynthesis, resulting in decreased hormone levels and growth inhibition. As a feedback mechanism, GA extensively inhibits BR biosynthesis and the BR response. GA treatment decreases the enlarged leaf angles in plants with enhanced BR biosynthesis or signaling. Our results revealed a previously unknown mechanism underlying BR and GA crosstalk depending on tissues and hormone levels, which greatly advances our understanding of hormone actions in crop plants and appears much different from that in Arabidopsis thaliana.     

S-Nitrosylation of Ascorbate Peroxidase Is Part of Programmed Cell Death Signaling in Tobacco Bright Yellow-2 Cells

Nitric oxide (NO) is a small redox molecule that acts as a signal in different physiological and stress-related processes in plants. Recent evidence suggests that the biological activity of NO is also mediated by S-nitrosylation, a well-known redox-based posttranslational protein modification. Here, we show that during programmed cell death (PCD), induced by both heat shock (HS) or hydrogen peroxide (H₂O₂) in tobacco (Nicotiana tabacum) Bright Yellow-2 cells, an increase in S-nitrosylating agents occurred. NO increased in both experimentally induced PCDs, although with different intensities. In H₂O₂-treated cells, the increase in NO was lower than in cells exposed to HS. However, a simultaneous increase in S-nitrosoglutathione (GSNO), another NO source for S-nitrosylation, occurred in H₂O₂-treated cells, while a decrease in this metabolite was evident after HS. Consistently, different levels of activity and expression of GSNO reductase, the enzyme responsible for GSNO removal, were found in cells subjected to the two different PCD-inducing stimuli: low in H₂O₂-treated cells and high in the heat-shocked ones. Irrespective of the type of S-nitrosylating agent, S-nitrosylated proteins formed upon exposure to both of the PCD-inducing stimuli. Interestingly, cytosolic ascorbate peroxidase (cAPX), a key enzyme controlling H₂O₂ levels in plants, was found to be S-nitrosylated at the onset of both PCDs. In vivo and in vitro experiments showed that S-nitrosylation of cAPX was responsible for the rapid decrease in its activity. The possibility that S-nitrosylation induces cAPX ubiquitination and degradation and acts as part of the signaling pathway leading to PCD is discussed.Nitric oxide (NO) is a gaseous and diffusible redox molecule that acts as a signaling compound in both animal and plant systems (Pacher et al., 2007; Besson-Bard et al., 2008). In plants, NO has been found to play a key role in several physiological processes, such as germination, lateral root development, flowering, senescence, stomatal closure, and growth of pollen tubes (Beligni and Lamattina, 2000; Neill et al., 2002; Correa-Aragunde et al., 2004; He et al., 2004; Prado et al., 2004; Carimi et al., 2005). In addition, NO has been reported to be involved in plant responses to both biotic and abiotic stresses (Leitner et al., 2009; Siddiqui et al., 2011) and in the signaling pathways leading to programmed cell death (PCD; Delledonne et al., 1998; de Pinto et al., 2006; De Michele et al., 2009; Lin et al., 2012; Serrano et al., 2012).The cellular environment may greatly influence the chemical reactivity of NO, giving rise to different biologically active NO-derived compounds, collectively named reactive nitrogen species, which amplify and differentiate its ability to activate physiological and stress-related processes. Many of the biological properties of NO are due to its high affinity with transition metals of metalloproteins as well as its reactivity with reactive oxygen species (ROS; Hill et al., 2010). However, recent evidence suggests that protein S-nitrosylation, due to the addition of NO to reactive Cys thiols, may act as a key mechanism of NO signaling in plants (Wang et al., 2006; Astier et al., 2011). NO is also able to react with reduced glutathione (GSH), the most abundant cellular thiol, thus producing S-nitrosoglutathione (GSNO), which also acts as an endogenous trans-nitrosylating agent. GSNO is also considered as a NO store and donor and, as it is more stable than NO, acts as a long-distance NO transporter through the floematic flux (Malik et al., 2011). S-Nitrosoglutathione reductase (GSNOR), which is an enzyme conserved from bacteria to humans, has been suggested to play a role in regulating S-nitrosothiols (SNO) and the turnover of S-nitrosylated proteins in plants (Liu et al., 2001; Rusterucci et al., 2007).A number of proteins involved in metabolism, stress responses, and redox homeostasis have been identified as potential targets for S-nitrosylation in Arabidopsis (Arabidopsis thaliana; Lindermayr et al., 2005). During the hypersensitive response (HR), 16 proteins were identified to be S-nitrosylated in the seedlings of the same species (Romero-Puertas et al., 2008); in Citrus species, S-nitrosylation of about 50 proteins occurred in the NO-mediated resistance to high salinity (Tanou et al., 2009).However, while the number of candidate proteins for S-nitrosylation is increasing, the functional significance of protein S-nitrosylation has been explained only in a few cases, such as for nonsymbiotic hemoglobin (Perazzolli et al., 2004), glyceraldehyde 3-phosphate dehydrogenase (Lindermayr et al., 2005; Wawer et al., 2010), Met adenosyltransferase (Lindermayr et al., 2006), and metacaspase9 (Belenghi et al., 2007). Of particular interest are the cases in which S-nitrosylation involves enzymes controlling ROS homeostasis. For instance, it has been reported that S-nitrosylation of peroxiredoxin IIE regulates the antioxidant function of this enzyme and might contribute to the HR (Romero-Puertas et al., 2007). It has also been shown that in the immunity response, S-nitrosylation of NADPH oxidase inactivates the enzyme, thus reducing ROS production and controlling HR development (Yun et al., 2011).Recently, S-nitrosylation has also been shown to be involved in PCD of nitric oxide excess1 (noe1) rice (Oryza sativa) plants, which are mutated in the OsCATC gene coding for catalase (Lin et al., 2012). In these plants, which show PCD-like phenotypes under high-light conditions, glyceraldehyde 3-phosphate dehydrogenase and thioredoxin are S-nitrosylated. This suggests that the NO-dependent regulation of these proteins is involved in plant PCD, similar to what occurs in animal apoptosis (Sumbayev, 2003; Hara et al., 2005; Lin et al., 2012). The increase in hydrogen peroxide (H₂O₂) after exposure to high light in noe1 plants is responsible for the production of NO required for leaf cell death induction (Lin et al., 2012). There is a strict relationship between H₂O₂ and NO in PCD activation (Delledonne et al., 2001; de Pinto et al., 2002); however, the mechanism of this interplay is largely still unknown (for review, see Zaninotto et al., 2006; Zhao, 2007; Yoshioka et al., 2011). NO can induce ROS production and vice versa, and their reciprocal modulation in terms of intensity and timing seems to be crucial in determining PCD activation and in controlling HR development (Delledonne et al., 2001; Zhao, 2007; Yun et al., 2011).In previous papers, we demonstrated that heat shock (HS) at 55°C and treatment with 50 mm H₂O₂ promote PCD in tobacco (Nicotiana tabacum) Bright Yellow-2 (BY-2) cells (Vacca et al., 2004; de Pinto et al., 2006; Locato et al., 2008). In both experimental conditions, NO production and decrease in cytosolic ascorbate peroxidase (cAPX) were observed as early events in the PCD pathway, and cAPX decrease has been suggested to contribute to determining the redox environment required for PCD (de Pinto et al., 2006; Locato et al., 2008).In this study, the production of nitrosylating agents (NO and GSNO) in the first hours of PCD induction by HS or H₂O₂ treatment in tobacco BY-2 cells and their role in PCD were studied. The possibility that S-nitrosylation could be a first step in regulating cAPX activity and turnover as part of the signaling pathway leading to PCD was also investigated.     

Structural Basis of Efficient Electron Transport between Photosynthetic Membrane Proteins and Plastocyanin in Spinach Revealed Using Nuclear Magnetic Resonance

In the photosynthetic light reactions of plants and cyanobacteria, plastocyanin (Pc) plays a crucial role as an electron carrier and shuttle protein between two membrane protein complexes: cytochrome b₆f (cyt b₆f) and photosystem I (PSI). The rapid turnover of Pc between cyt b₆f and PSI enables the efficient use of light energy. In the Pc-cyt b₆f and Pc-PSI electron transfer complexes, the electron transfer reactions are accomplished within <10⁻⁴ s. However, the mechanisms enabling the rapid association and dissociation of Pc are still unclear because of the lack of an appropriate method to study huge complexes with short lifetimes. Here, using the transferred cross-saturation method, we investigated the residues of spinach (Spinacia oleracea) Pc in close proximity to spinach PSI and cyt b₆f, in both the thylakoid vesicle–embedded and solubilized states. We demonstrated that the hydrophobic patch residues of Pc are in close proximity to PSI and cyt b₆f, whereas the acidic patch residues of Pc do not form stable salt bridges with either PSI or cyt b₆f, in the electron transfer complexes. The transient characteristics of the interactions on the acidic patch facilitate the rapid association and dissociation of Pc.     

The Operation of Two Decarboxylases,Transamination, and Partitioning of C4 Metabolic Processes between Mesophyll and Bundle Sheath Cells Allows Light Capture To Be Balanced for the Maize C4 Pathway

The C₄ photosynthesis carbon-concentrating mechanism in maize (Zea mays) has two CO₂ delivery pathways to the bundle sheath (BS; via malate or aspartate), and rates of phosphoglyceric acid reduction, starch synthesis, and phosphoenolpyruvate regeneration also vary between BS and mesophyll (M) cells. The theoretical partitioning of ATP supply between M and BS cells was derived for these metabolic activities from simulated profiles of light penetration across a leaf, with a potential 3-fold difference in the fraction of ATP produced in the BS relative to M (from 0.29 to 0.96). A steady-state metabolic model was tested using varying light quality to differentially stimulate M or BS photosystems. CO₂ uptake, ATP production rate (J_ATP; derived with a low oxygen/chlorophyll fluorescence method), and carbon isotope discrimination were measured on plants under a low light intensity, which is considered to affect C₄ operating efficiency. The light quality treatments did not change the empirical ATP cost of gross CO₂ assimilation (J_ATP/GA). Using the metabolic model, measured J_ATP/GA was compared with the predicted ATP demand as metabolic functions were varied between M and BS. Transamination and the two decarboxylase systems (NADP-malic enzyme and phosphoenolpyruvate carboxykinase) were critical for matching ATP and reduced NADP demand in BS and M when light capture was varied under contrasting light qualities.Interest in the C₄ pathway has been increased by the potential for enhancing crop productivity and maintaining yield stability in the face of global warming and population pressure (Friso et al., 2010; Zhu et al., 2010; Covshoff and Hibberd, 2012). Maize (Zea mays), a C₄ plant of the NADP-malic enzyme (ME) subtype, is a leading grain production cereal (www.fao.org). C₄ photosynthesis is a shared activity between mesophyll (M; abbreviations are listed in BS) cells, coupled to allow the operation of a biochemical carbon-concentrating mechanism (CCM). The CCM effectively minimizes photorespiration by increasing the CO₂ concentration in the bundle sheath (C_BS), where Rubisco is exclusively expressed. Since BS and M are connected by plasmodesmata, some CO₂ retrodiffuses. The refixation of that escaping CO₂ by the CCM increases the activity of the CCM and the total ATP demand (ATP_BS + ATP_M) for gross CO₂ assimilation (GA; [ATP_BS + ATP_M]/GA), from a theoretical minimum of five ATPs (Furbank et al., 1990). Leakiness (Φ), the amount of CO₂ retrodiffusing relative to phosphoenolpyruvate (PEP) carboxylation rate, is therefore a proxy for the coordination between the CCM and assimilatory activity (Henderson et al., 1992; Tazoe et al., 2008; Kromdijk et al., 2010; Ubierna et al., 2011; Bellasio and Griffiths, 2013).

Table I.

Variables and acronyms described in the text

One Divinyl Reductase Reduces the 8-Vinyl Groups in Various Intermediates of Chlorophyll Biosynthesis in a Given Higher Plant Species,But the Isozyme Differs between Species

Divinyl reductase (DVR) converts 8-vinyl groups on various chlorophyll intermediates to ethyl groups, which is indispensable for chlorophyll biosynthesis. To date, five DVR activities have been detected, but adequate evidence of enzymatic assays using purified or recombinant DVR proteins has not been demonstrated, and it is unclear whether one or multiple enzymes catalyze these activities. In this study, we systematically carried out enzymatic assays using four recombinant DVR proteins and five divinyl substrates and then investigated the in vivo accumulation of various chlorophyll intermediates in rice (Oryza sativa), maize (Zea mays), and cucumber (Cucumis sativus). The results demonstrated that both rice and maize DVR proteins can convert all of the five divinyl substrates to corresponding monovinyl compounds, while both cucumber and Arabidopsis (Arabidopsis thaliana) DVR proteins can convert three of them. Meanwhile, the OsDVR (Os03g22780)-inactivated 824ys mutant of rice exclusively accumulated divinyl chlorophylls in its various organs during different developmental stages. Collectively, we conclude that a single DVR with broad substrate specificity is responsible for reducing the 8-vinyl groups of various chlorophyll intermediates in higher plants, but DVR proteins from different species have diverse and differing substrate preferences, although they are homologous.Chlorophyll (Chl) molecules universally exist in photosynthetic organisms. As the main component of the photosynthetic pigments, Chl molecules perform essential processes of absorbing light and transferring the light energy in the reaction center of the photosystems (Fromme et al., 2003). Based on the number of vinyl side chains, Chls are classified into two groups, 3,8-divinyl (DV)-Chl and 3-monovinyl (MV)-Chl. The DV-Chl molecule contains two vinyl groups at positions 3 and 8 of the tetrapyrrole macrocycle, whereas the MV-Chl molecule contains a vinyl group at position 3 and an ethyl group at position 8 of the macrocycle. Almost all of the oxygenic photosynthetic organisms contain MV-Chls, with the exceptions of some marine picophytoplankton species that contain only DV-Chls as their primary photosynthetic pigments (Chisholm et al., 1992; Goericke and Repeta, 1992; Porra, 1997).The classical single-branched Chl biosynthetic pathway proposed by Granick (1950) and modified by Jones (1963) assumed the rapid reduction of the 8-vinyl group of DV-protochlorophyllide (Pchlide) catalyzed by a putative 8-vinyl reductase. Ellsworth and Aronoff (1969) found evidence for both MV and DV forms of several Chl biosynthetic intermediates between magnesium-protoporphyrin IX monomethyl ester (MPE) and Pchlide in Chlorella spp. mutants. Belanger and Rebeiz (1979, 1980) reported that the Pchlide pool of etiolated higher plants contains both MV- and DV-Pchlide. Afterward, following the further detection of MV- and DV-tetrapyrrole intermediates and their biosynthetic interconversion in tissues and extracts of different plants (Belanger and Rebeiz, 1982; Duggan and Rebeiz, 1982; Tripathy and Rebeiz, 1986, 1988; Parham and Rebeiz, 1992, 1995; Kim and Rebeiz, 1996), a multibranched Chl biosynthetic heterogeneity was proposed (Rebeiz et al., 1983, 1986, 1999; Whyte and Griffiths, 1993; Kolossov and Rebeiz, 2010).Biosynthetic heterogeneity refers to the biosynthesis of a particular metabolite by an organelle, tissue, or organism via multiple biosynthetic routes. Varieties of reports lead to the assumption that Chl biosynthetic heterogeneity originates mainly in parallel DV- and MV-Chl biosynthetic routes. These routes are interconnected by 8-vinyl reductases that convert DV-tetrapyrroles to MV-tetrapyrroles by conversion of the vinyl group at position 8 of ring B to the ethyl group (Parham and Rebeiz, 1995; Rebeiz et al., 2003). DV-MPE could be converted to MV-MPE in crude homogenates from etiolated wheat (Triticum aestivum) seedlings (Ellsworth and Hsing, 1974). Exogenous DV-Pchlide could be partially converted to MV-Pchlide in barley (Hordeum vulgare) plastids (Tripathy and Rebeiz, 1988). 8-Vinyl chlorophyllide (Chlide) a reductases in etioplast membranes isolated from etiolated cucumber (Cucumis sativus) cotyledons and barley and maize (Zea mays) leaves were found to be very active in the conversion of exogenous DV-Chlide a to MV-Chlide a (Parham and Rebeiz, 1992, 1995). Kim and Rebeiz (1996) suggested that Chl biosynthetic heterogeneity in higher plants may originate at the level of DV magnesium-protoporphyrin IX (Mg-Proto) and would be mediated by the activity of a putative 8-vinyl Mg-Proto reductase in barley etiochloroplasts and plastid membranes. However, since these reports did not use purified or recombinant enzyme, it is not clear whether the reductions of the 8-vinyl groups of various Chl intermediates are catalyzed by one enzyme of broad specificity or by multiple enzymes of narrow specificity, which actually has become one of the focus issues in Chl biosynthesis.Nagata et al. (2005) and Nakanishi et al. (2005) independently identified the AT5G18660 gene of Arabidopsis (Arabidopsis thaliana) as an 8-vinyl reductase, namely, divinyl reductase (DVR). Chew and Bryant (2007) identified the DVR BciA (CT1063) gene of the green sulfur bacterium Chlorobium tepidum, which is homologous to AT5G18660. An enzymatic assay using a recombinant Arabidopsis DVR (AtDVR) on five DV substrates revealed that the major substrate of AtDVR is DV-Chlide a, while the other four DV substrates could not be converted to corresponding MV compounds (Nagata et al., 2007). Nevertheless, a recombinant BciA is able to reduce the 8-vinyl group of DV-Pchlide to generate MV-Pchlide (Chew and Bryant, 2007). Recently, we identified the rice (Oryza sativa) DVR encoded by Os03g22780 that has sequence similarity with the Arabidopsis DVR gene AT5G18660. We also confirmed that the recombinant rice DVR (OsDVR) is able to not only convert DV-Chlide a to MV-Chlide a but also to convert DV-Chl a to MV-Chl a (Wang et al., 2010). Thus, it is possible that the reductions of the 8-vinyl groups of various Chl biosynthetic intermediates are catalyzed by one enzyme of broad specificity.In this report, we extended our studies to four DVR proteins and five DV substrates. First, ZmDVR and CsDVR genes were isolated from maize and cucumber genomes, respectively, using a homology-based cloning approach. Second, enzymatic assays were systematically carried out using recombinant OsDVR, ZmDVR, CsDVR, and AtDVR as representative DVR proteins and using DV-Chl a, DV-Chlide a, DV-Pchlide a, DV-MPE, and DV-Mg-Proto as DV substrates. Third, we examined the in vivo accumulations of various Chl intermediates in rice, maize, and cucumber. Finally, we systematically investigated the in vivo accumulations of Chl and its various intermediates in the OsDVR (Os03g22780)-inactivated 824ys mutant of rice (Wang et al., 2010). The results strongly suggested that a single DVR protein with broad substrate specificity is responsible for reducing the 8-vinyl groups of various intermediate molecules of Chl biosynthesis in higher plants, but DVR proteins from different species could have diverse and differing substrate preferences even though they are homologous.     

Nitrogen Stress Affects the Turnover and Size of Nitrogen Pools Supplying Leaf Growth in a Grass

The effect of nitrogen (N) stress on the pool system supplying currently assimilated and (re)mobilized N for leaf growth of a grass was explored by dynamic ¹⁵N labeling, assessment of total and labeled N import into leaf growth zones, and compartmental analysis of the label import data. Perennial ryegrass (Lolium perenne) plants, grown with low or high levels of N fertilization, were labeled with ¹⁵NO₃⁻/¹⁴NO₃⁻ from 2 h to more than 20 d. In both treatments, the tracer time course in N imported into the growth zones fitted a two-pool model (r² > 0.99). This consisted of a “substrate pool,” which received N from current uptake and supplied the growth zone, and a recycling/mobilizing “store,” which exchanged with the substrate pool. N deficiency halved the leaf elongation rate, decreased N import into the growth zone, lengthened the delay between tracer uptake and its arrival in the growth zone (2.2 h versus 0.9 h), slowed the turnover of the substrate pool (half-life of 3.2 h versus 0.6 h), and increased its size (12.4 μg versus 5.9 μg). The store contained the equivalent of approximately 10 times (low N) and approximately five times (high N) the total daily N import into the growth zone. Its turnover agreed with that of protein turnover. Remarkably, the relative contribution of mobilization to leaf growth was large and similar (approximately 45%) in both treatments. We conclude that turnover and size of the substrate pool are related to the sink strength of the growth zone, whereas the contribution of the store is influenced by partitioning between sinks.This article examines the nitrogen (N) supply system of growing grass leaves, and it investigates how functional and kinetic properties of this system are affected by N stress. The N supply of growing leaves is a dominant target of whole-plant N metabolism. This is primarily related to the high N demand of the photosynthetic apparatus and the related metabolic machinery of new leaves (Evans, 1989; Makino and Osmond, 1991; Grindlay, 1997; Lemaire, 1997; Wright et al., 2004; Johnson et al., 2010; Maire et al., 2012). The N supply system, as defined here, is an integral part of the whole plant: it includes all N compounds that supply leaf growth. Hence, it integrates all events between the uptake of N from the environment (source), intermediate uses in other processes of plant N metabolism, and the eventual delivery to the leaf growth zone (sink; Fig. 1). N that does not ultimately serve leaf growth is not included in this system; all N that serves leaf growth is included, irrespective of its localization in the plant. Conceptually, two distinct sources supply N for leaf growth: N from current uptake and assimilation that is directly transferred to the growing leaf (“directly transferred N”) and N from turnover/redistribution of organic compounds (“mobilized N”).Open in a separate windowFigure 1.Schematic representation of N fluxes in the leaf growth zone and in the N supply system of leaf growth in a grass plant. A, Scheme of a growing leaf, with its growth zone (including zones of cell division, expansion, and maturation) and recently produced tissue (RPT). N import (I; μg h⁻¹) into the growth zone is mostly in the form of amino acids. Inside the growth zone, the nitrogenous substrate is used in new tissue construction. Then, N export (E; μg h⁻¹) is in the form of newly formed, fully expanded nitrogenous tissue (tissue-bound export with RPT) and is calculated as leaf elongation rate (L_ER; mm h⁻¹) times the lineal density of N in RPT (ρ; μg mm⁻¹): E = L_ER × ρ (Lattanzi et al., 2004). In a physiological steady state, import equals export (I = E) and the N content of the growth zone (G; μg [not shown]) is constant. Labeled N import into the growth zone (I_lab) commences shortly after labeling of the nutrient solution with ¹⁵N. The labeled N content of the growth zone (G_lab; μg) increases over time (dG_lab/dt) until it eventually reaches isotopic saturation (Fig. 2B). Similarly, the lineal density of labeled N in RPT (ρ_lab) increases until it approaches ρ. At any time, the export of labeled N in RPT (E_lab) equals the concurrent ρ_lab × L_ER. The import of labeled N is obtained as I_lab = E_lab + dG_lab/dt (Lattanzi et al., 2005) and considers the increasing label content in the growth zone during labeling. The fraction of labeled N in the import flux (f_{lab I}) is calculated as f_{lab I} = I_lab/I. The time course of f_{lab I} (Fig. 3) reflects the kinetic properties of the N supply system of leaf growth (C). B, Scheme of a vegetative grass plant (reduced to a rooted tiller with three leaves) with leaf growth zone. N import into the growth zone (I) originates from (1) N taken up from the nutrient solution that is transferred directly to the growth zone following assimilation (directly transferred N) and (2) N derived from turnover/redistribution of stores (mobilized N). The store potentially includes proteins in all mature and senescing tissue in the shoot and root of the entire plant. As xylem, phloem, and associated transfer cells/tissue provide for a vascular network that connects all parts of the plant, the mobilized N may principally originate from any plant tissue that exhibits N turnover/mobilization. The fraction of total N uptake that is allocated to the N supply system of the growth zone equals U (see model in C). The fraction of total mobilized N allocated to the growth zone equals M (see model in C). C, Compartmental model of the source-sink system supplying N to the leaf growth zone, as shown by Lattanzi et al. (2005) and used here. Newly absorbed N (U; μg h⁻¹) enters a substrate pool (Q₁); from there, the N is either imported directly into the growth zone (I) or exchanged with a store (Q₂). Q₁ integrates the steps of transport and assimilation that precede the translocation to the growth zone. Q₂ includes all proteins that supply N for leaf growth during their turnover and mobilization. The parameters of the model, including the (relative) size and turnover of pools Q₁ and Q₂, the deposition into the store (D; μg h⁻¹), and the mobilization from the store (M; μg h⁻¹), and the contribution of direct transfer relative to mobilization to the N supply of the growth zone are obtained by fitting the compartmental model to the f_{lab I} data (A) obtained in dynamic ¹⁵N labeling experiments (for details, see “Materials and Methods”). During physiological steady state, the sizes of Q₁ and Q₂ are constant, I = U, and M = D. [See online article for color version of this figure.]Amino acids are the predominant form in which N is supplied for leaf growth in grasses, and incorporation in new leaf tissue occurs mainly in the leaf growth zone (Gastal and Nelson, 1994; Amiard et al., 2004). This is a heterotrophic piece of tissue that includes the zones of cell division and elongation, is located at the base of the leaf, and is encircled by the sheath of the next older leaf (Volenec and Nelson, 1981; MacAdam et al., 1989; Schnyder et al., 1990; Kavanová et al., 2008). As most N is taken up in the form of nitrate but supplied to the growth zone in the form of amino acids, the path of directly transferred N includes a series of metabolic and transport steps. These include transfer to and loading into the xylem, xylem transport and unloading, reduction and ammonium assimilation, cycling through photorespiratory N pools, amino acid synthesis, loading into the phloem, and transport to the growth zone (Hirel and Lea, 2001; Novitskaya et al., 2002; Stitt et al., 2002; Lalonde et al., 2003; Dechorgnat et al., 2011). The time taken to pass through this sequence is unknown at present, as is the effect of N deficiency on that time. Also, it is not known how much N is contained in, and moving through, the different compartments that supply leaf growth with currently assimilated N.At the level of mature organs, mainly leaves, there is considerable knowledge about N turnover and redistribution. Much less is known about the fate of the mobilized N and its actual use in sink tissues like the leaf growth zone. The processes in mature organs are associated with the maintenance metabolism of proteins, organ senescence, and adjustments in leaf protein levels to decreasing irradiance inside growing canopies when leaves become shaded by overtopping newer ones (Evans, 1993; Vierstra, 1993; Hikosaka et al., 1994; Anten et al., 1995; Hirel et al., 2007; Jansson and Thomas, 2008; Moreau et al., 2012). N mobilization in shaded leaves supports the optimization of photosynthetic N use efficiency at plant and canopy scale (Field, 1983; Evans, 1993; Anten et al., 1995), it reduces the respiratory burden of protein maintenance costs (Dewar et al., 1998; Amthor, 2000; Cannell and Thornley, 2000), and it provides a mechanism for the conservation of the most frequently growth-limiting nutrient (Aerts, 1996). Mobilization of N involves protein turnover and net degradation (Huffaker and Peterson, 1974), redistribution in the form of amino acids (Simpson and Dalling, 1981; Simpson et al., 1983; Hörtensteiner and Feller, 2002), and (at least) some of the mobilized N is supplied to new leaf growth (Lattanzi et al., 2005).N fertilizer supply has multiple direct and indirect effects on plant N metabolism (Stitt et al., 2002; Schlüter et al., 2012). In particular, it modifies the N content of newly produced leaves, leaf longevity/senescence, and the dynamics of light distribution inside expanding canopies (Evans, 1983, 1989; Lötscher et al., 2003; Moreau et al., 2012). Thus, N fertilization influences the availability of recyclable N. At the same time, it augments the availability of directly transferable N to leaf growth. The net effect of these factors on the importance of mobilized versus directly transferred N substrate for leaf growth is not known. Also, it is unknown how N fertilization influences the functional characteristics of the N supply system, such as the size and turnover of its component pools.The assessment of the importance of directly transferred versus mobilized N for leaf growth requires studies at the sink end of the system (i.e. investigations of the N import flux into the leaf growth zone). Directly transferred N and mobilized N can be distinguished on the basis of their residence time in the plant, the time between uptake from the environment and import into the leaf growth zone: direct transfer involves a short residence time (fast transfer), whereas mobilized N resides much longer in the plant before it is delivered to the growth zone (slow transfer; De Visser et al., 1997; Lattanzi et al., 2005). Such studies require dynamic labeling of the N taken up by the plant (Schnyder and de Visser, 1999) and monitoring of the rate and isotopic composition/label content of N import into the leaf growth zone (Lattanzi et al., 2005). For grass plants in a physiological steady state, N import and the isotopic composition of the imported N are calculated from the leaf elongation rate and the lineal density of N in newly formed tissue (Fig. 1A; Lattanzi et al., 2004) and the change of tracer content in the leaf growth zone and recently produced leaf tissue over time (Lattanzi et al., 2005). Such data reveal the temporal change of the fraction of labeled N in the N import flux (f_{lab I}), which then can be used to characterize the N supply system of leaf growth via compartmental modeling. So far, there is only one study that has partially characterized this system (Lattanzi et al., 2005): this work was conducted with a C₃ grass, perennial ryegrass (Lolium perenne), and a C₄ grass, Paspalum dilatatum, growing in mixed stands and indicated that two interconnected N pools supplied the leaf growth zone in both species: a “substrate pool” (Q₁), which provided a direct route for newly absorbed and assimilated N import into the leaf growth zone (directly transferred N), and a mobilizing “store” (Q₂), which supplied N to the leaf growth zone via the substrate pool (Fig. 1C). The relative contribution of mobilization from the store was least important in the fast-growing, dominant individuals and most important in subordinate, shaded individuals. That work did not address the role of N deficiency, and the limited short-term resolution of the study (labeling intervals of 24 h or greater) precluded an analysis of the fast-moving parts of the system.Accordingly, this work addresses the following questions. How does N deficiency influence the substrate supply system of the leaf growth sink in terms of the number, size, and turnover (half-life) of its kinetically distinct pools? How does N deficiency affect the relationship between directly transferred and mobilized N for leaf growth? And what additional insight on the compartmental structure of the supply system is obtained when the short-term resolution of the analysis is increased by 1 order of magnitude? The work was performed with vegetative plants of perennial ryegrass grown in constant conditions with either a low (1.0 mm; termed low N) or high (7.5 mm; high N) nitrate concentration in the nutrient solution. In both treatments, a large number of plants were dynamically labeled with ¹⁵N over a wide range of time intervals (2 h to more than 20 d). The import of total N and ¹⁵N tracer into growth zones was estimated at the end of each labeling interval. Tracer data were analyzed with compartmental models following principles detailed by Lattanzi et al. (2005, 2012) and Lehmeier et al. (2008) to address the specific questions. Previous articles reported on root and shoot respiration (Lehmeier et al., 2010) and cell division and expansion in leaf growth zones (Kavanová et al., 2008) in the same experiment.     

Last-Century Increases in Intrinsic Water-Use Efficiency of Grassland Communities Have Occurred over a Wide Range of Vegetation Composition,Nutrient Inputs,and Soil pH

Last-century climate change has led to variable increases of the intrinsic water-use efficiency (W_i; the ratio of net CO₂ assimilation to stomatal conductance for water vapor) of trees and C₃ grassland ecosystems, but the causes of the variability are not well understood. Here, we address putative drivers underlying variable W_i responses in a wide range of grassland communities. W_i was estimated from carbon isotope discrimination in archived herbage samples from 16 contrasting fertilizer treatments in the Park Grass Experiment, Rothamsted, England, for the 1915 to 1929 and 1995 to 2009 periods. Changes in W_i were analyzed in relation to nitrogen input, soil pH, species richness, and functional group composition. Treatments included liming as well as phosphorus and potassium additions with or without ammonium or nitrate fertilizer applications at three levels. W_i increased between 11% and 25% (P < 0.001) in the different treatments between the two periods. None of the fertilizers had a direct effect on the change of W_i (ΔW_i). However, soil pH (P < 0.05), species richness (P < 0.01), and percentage grass content (P < 0.01) were significantly related to ΔW_i. Grass-dominated, species-poor plots on acidic soils showed the largest ΔW_i (+14.7 μmol mol⁻¹). The ΔW_i response of these acidic plots was probably related to drought effects resulting from aluminum toxicity on root growth. Our results from the Park Grass Experiment show that W_i in grassland communities consistently increased over a wide range of nutrient inputs, soil pH, and plant community compositions during the last century.The intrinsic water-use efficiency (W_i) of plants is controlled by photosynthetic carbon assimilation and stomatal conductance via the leaf-level coupling of CO₂ and water fluxes. A general, but variable, increase of W_i under rising atmospheric CO₂ has been observed in long-term studies (Peñuelas et al., 2011; Franks et al., 2013; Saurer et al., 2014), but little is known about other environmental or ecosystem factors, which may interact with the effect of increasing CO₂ on W_i. An improved understanding of putative interactive mechanisms is important because changes in W_i may have significant effects on the global terrestrial carbon and water cycles (Gedney et al., 2006; Betts et al., 2007). This study explores the interactive effects of the increase in atmospheric CO₂ (observed over the last century), nutrient loading, and soil pH together with other related effects on plant species richness and functional group composition on the coupling of plant CO₂ and water fluxes in a seminatural grassland in southeastern England.W_i is a leaf-level efficiency that has also been termed potential water-use efficiency or physiological water-use efficiency, as it excludes the direct influence of vapor pressure deficit (VPD), a parameter determined by environmental conditions, on leaf-level water-use efficiency (Farquhar et al., 1989; Franks et al., 2013). W_i reports the relationship between net CO₂ assimilation rate (A_n) and stomatal conductance for water vapor (g_H2O):(1)According to the first law of Fick, A_n can be given as the product of the stomatal conductance for CO₂ (g_CO2) and the concentration gradient between the atmosphere (c_a) and the leaf internal gas space (c_i): A_n= g_CO2 (c_a – c_i). Using g_CO2 (c_a – c_i) instead of A_n in Equation 1, replacement of g_H2O/g_CO2 by the numerical value of g_H2O/g_CO2 (1.6) and rearrangement yields the following alternative expression of W_i:(2)Equation 2 reveals that past changes of W_i must have been controlled by two parameters: the change of c_a and the concurrent change of 1 – c_i/c_a, the relative gradient for CO₂ diffusion into the leaf (Franks et al., 2013). A change in the relative gradient is determined by the changes in A_n relative to g_H2O, as leaves respond to changing c_a and other environmental factors. In particular, Equation 2 shows that any variation in the climate change response of W_i is determined by the c_i/c_a response, if the comparison is made for vegetation at the same location and in the same period of time.Studies with C₃ vegetation, including trees/forests and C₃ grasslands, have revealed a general increase of W_i in the last century (Bert et al., 1997; Duquesnay et al., 1998; Feng, 1999; Arneth et al., 2002; Saurer et al., 2004; Barbosa et al., 2010; Köhler et al., 2010; Andreu-Hayles et al., 2011). In many cases, c_i/c_a, estimated by ¹³C discrimination (Farquhar et al., 1989), varied relatively little. Indeed, it has been suggested, based on theoretical grounds and empirical evidence from studies over geological/evolutionary to short time scales, that adaptive feedback responses will tend to maintain c_i/c_a approximately constant (Ehleringer and Cerling, 1995; Franks et al., 2013), as plants optimize carbon gain with respect to water loss (Cowan and Farquhar, 1977). Yet, c_i/c_a-dependent variation in the W_i response to climate change has also been noted (Peñuelas et al., 2011; Köhler et al., 2012) over the last century, indicating that additional factors, perhaps including other global change drivers, can modify the W_i response over this time scale, at least transiently. A meta-analysis by Peñuelas et al. (2011) reports c_i/c_a-dependent increases of W_i for different forests between 6% and 36% from the early 1960s to 2000s. A recent study by Saurer et al. (2014) on European forest trees found increases in W_i ranging from 1% to 53% during the last century. The strongest increase of W_i was recorded in regions where summer soil-water availability decreased in the last century. For different grassland communities, the c_i/c_a-dependent increases of W_i varied between 13% and 28% at one site (Köhler et al., 2012) from 1915 to 2009. Evidently, such variation can have important repercussions for the coupling of terrestrial CO₂ and water fluxes. Yet, little is known about the mechanism(s) underlying the variation.At the Park Grass Experiment (PGE) at Rothamsted, England, Köhler et al. (2012) observed a nitrogen supply-dependent enhancement of the W_i response on plots receiving nitrate fertilizer and maintained at a near-neutral soil pH by liming. However, the actual relationship between nitrogen supply and W_i response did not hold when the unlimed control (soil pH approximately 5.2) was included in the comparison. Remarkably, however, there was a significant positive relationship between the grass content of the community and the W_i response of the experimental plots in the investigation. These results suggested that the effect of nutrient supply on the W_i response of the grassland communities was indirect, perhaps working via effects on soil pH and/or vegetation composition (plant species richness or functional group composition).The PGE provides a unique opportunity to study century-scale variation in the c_i/c_a-dependent variation of W_i for a wide range of diverse grassland communities. Much of the extant ecosystem-scale variability of plant species richness and soil pH in temperate grasslands of Europe (Ceulemans et al., 2014) is included in the range of plot-scale plant species richness and soil pH at the PGE (which is reported in this investigation). The different long-term applications of fertilizer and lime over the past century have resulted in substantial changes in soil pH, species richness, and grass content on the experimental plots, but in most cases, within-plot changes over the study period considered here (1915–2009) were comparatively small (Crawley et al., 2005; Silvertown et al., 2006). All experimental plots are located at the same site and are exposed to the same weather conditions. Consequently, trends in climate as a direct driver for differences in W_i between plots can be ruled out.Here, we explore putative mechanisms underlying eventual c_i/c_a-dependent variation of W_i during the last century at the PGE by, first, quantifying the sustained effect of a wide range of contrasting fertilizer treatments (n = 16) on the change of W_i during the last century and, second, analyzing the relationships between the observed W_i response of treatments and the respective nutrient status, soil pH, plant species richness, and plant functional group composition of the grassland communities.     

Acclimation of Leaf Nitrogen to Vertical Light Gradient at Anthesis in Wheat Is a Whole-Plant Process That Scales with the Size of the Canopy

Vertical leaf nitrogen (N) gradient within a canopy is classically considered as a key adaptation to the local light environment that would tend to maximize canopy photosynthesis. We studied the vertical leaf N gradient with respect to the light gradient for wheat (Triticum aestivum) canopies with the aims of quantifying its modulation by crop N status and genetic variability and analyzing its ecophysiological determinants. The vertical distribution of leaf N and light was analyzed at anthesis for 16 cultivars grown in the field in two consecutive seasons under two levels of N. The N extinction coefficient with respect to light (b) varied with N supply and cultivar. Interestingly, a scaling relationship was observed between b and the size of the canopy for all the cultivars in the different environmental conditions. The scaling coefficient of the b-green area index relationship differed among cultivars, suggesting that cultivars could be more or less adapted to low-productivity environments. We conclude that the acclimation of the leaf N gradient to the light gradient is a whole-plant process that depends on canopy size. This study demonstrates that modeling leaf N distribution and canopy expansion based on the assumption that leaf N distribution parallels that of the light is inappropriate. We provide a robust relationship accounting for vertical leaf N gradient with respect to vertical light gradient as a function of canopy size.In cereals, as in many crop species, nitrogen (N) nutrition is a major determinant in the elaboration of grain yield and quality (Lemaire and Millard, 1999; Lawlor, 2002; Hikosaka, 2005). N is involved in both meristematic and photosynthetic activities, with consequences on plant architecture and carbon acquisition and in fine on grain yield and protein concentration. Beside the total amount of N absorbed by the crop, the allocation of N among plant organs plays a key role in determining crop productivity and quality (Grindlay, 1997; Dreccer et al., 1998; Hikosaka, 2005).Light interception and leaf N content are the two main factors governing carbon assimilation at the leaf scale (Evans, 1989). For various species, both light and leaf N attenuate with cumulative leaf area index counted from the top of the canopy (Field, 1983; Hirose and Werger, 1987). Leaf N vertical gradients have been regarded as an adaptive response to the local light environment, maximizing canopy photosynthesis and N utilization efficiency (Hirose and Werger, 1987; Hikosaka et al., 1994; Drouet and Bonhomme, 1999), as N is largely contained in the assimilatory enzyme Rubisco. Theoretical studies indicated that leaf N maximizes canopy photosynthesis when it parallels the light gradient (i.e. when the light [K_L] and N [K_N] extinction coefficients are equal), considering that the leaf N gradient is “optimal” in accordance with the “optimization theory” (Field, 1983; Hirose and Werger, 1987; Anten et al., 1995b).Factors other than the photosynthetic photon flux density (PPFD) might be responsible for the observed leaf N distribution. For instance, the acropetal gradients of leaf age (Hikosaka et al., 1994; Hikosaka, 2005) and light composition (Rousseaux et al., 1999) are known to strengthen the leaf N gradient. However, the impact of each of these factors has been shown to be much less than that of the PPFD gradient (Werger and Hirose, 1991; Pons and de Jong-van Berkel, 2004), although for the grass species Brachypodium pinnatum other factors than light might be involved (Pons et al., 1993). At the molecular level, the process could be driven by the import of compounds such as cytokinins transported in the transpiration stream (Pons et al., 2001; Boonman et al., 2007). Although the actual N distribution usually follows the light gradient, in all studies it is less steep than the calculated optimal N profile maximizing canopy photosynthesis (Pons et al., 1989; Yin et al., 2003). Possible reasons for this discrepancy have been discussed in detail by Kull (2002). Sink-source relations and in particular the demand for N could modulate the light-leaf N relationship (Dreccer et al., 1998), but conflicting results have been reported regarding the effect of N availability on the light-leaf N relationship. While some authors found no effect of N availability (Sinclair and Shiraiwa, 1993; Milroy et al., 2001), others found that the N gradient relative to light (i.e. K_L/K_N) was steeper under low N (Hikosaka et al., 1994; Grindlay et al., 1995; Lötscher et al., 2003) or that the response of the light-leaf N relationship to N availability depended on the developmental stage (Dreccer et al., 2000). Interspecific differences in the light-leaf N relationship have also been reported and were related to differences in phenotypic plasticity (Aerts, 1996) or plant architecture (leaf stature and branching pattern; Anten et al., 1995a; Lötscher et al., 2003).Since canopy photosynthesis is dependent upon the leaf N gradient, it has been suggested that the pattern of leaf N distribution could be responsible for part of the genetic variability associated with the negative correlation between grain yield and protein concentration reported for various crop species (Dreccer et al., 1998). In wheat (Triticum aestivum), N accumulated before anthesis contributes 30% to 70% of grain N (Mi et al., 2000; Kichey et al., 2007). The efficiency of N translocation from the lower to the upper leaves may increase with the steepness of the N gradient, with only a negligible effect on canopy carbon gain integrated over the whole grain-filling period. This hypothesis is consistent with experimental studies based on a range of genotypes showing that, at a given grain yield level, grain protein concentration is positively related to the efficiency of N translocation either from the lower to the upper leaves (Wang et al., 2005) or from the leaves to the grains (Monaghan et al., 2001; Jukanti and Fischer, 2008). Only a few studies have investigated the intraspecific variability of the light-N relationship at the intraspecific level (Shiraiwa and Sinclair, 1993; Bindraban, 1999; Bertheloot et al., 2008; van Oosterom et al., 2010). For wheat, published analyses of the genetic variability of the light-leaf N relationship were limited to only two to five genotypes, and no genetic differences were found (Bindraban, 1999; Bertheloot et al., 2008).This paper focuses on the genetic variability of the vertical leaf N gradient with respect to light for wheat. Three main issues were investigated. What is the effect of N supply on the vertical distribution of leaf N? Does the distribution of leaf N with respect to light differ among genotypes? If the adjustment of leaf N to the light gradient varies with both the genotype and N supply, could this genetic and environmental variability have a unique ecophysiological determinant (driving variable)?These questions were addressed using 16 genotypes (Supplemental Table S1) covering a wide range of variation for N use efficiency (i.e. grain dry mass yield per unit of available mineral N from the soil and fertilizer), for grain protein concentration (Le Gouis et al., 2000; Foulkes et al., 2006; Gaju et al., 2011) and for the deviation from the negative correlation between grain yield and protein concentration (Oury et al., 2003). The 16 genotypes were grown in the field under two conditions of N supply (N− and N+ for low- and high-N treatments, respectively) in order to modulate crop N status at Clermont-Ferrand (CF) in France in two consecutive seasons (experiments CF07 and CF08). In addition, four of the 16 cultivars representing the variability observed for N utilization and N uptake efficiency were grown in the field under two conditions of N supply at Sutton Bonington (SB) in the United Kingdom in one season (experiment SB07). The distribution of leaf N was analyzed at anthesis. The first reason for this is that the distribution of both light and leaf N within the canopy is relatively stable from this phenological stage until almost the end of grain filling (Bertheloot et al., 2008). Whereas the canopy green area index (GAI) decreases dramatically during the grain-filling period, the structure of the canopy affecting light interception does not change significantly during that period. Both the vertical light and N distributions down the canopy are unchanged during most of the grain-filling period; therefore, the K_N-to-K_L ratio is constant during that period (Bertheloot et al., 2008). Similarly, Archontoulis et al. (2011) showed that K_N-to-K_L ratio is not modified during the vegetative and reproductive stages for field-gown sunflower (Helianthus annuus) crops. Therefore, as most of the final grain yield results from carbon assimilated after anthesis (Bidinger et al., 1977; Gebbing and Schnyder, 1999), the N distribution at anthesis is very relevant in terms of carbon assimilation and grain yield in wheat. A second reason is that the number and potential size of grains are determined around anthesis, which therefore appears as a critical stage in the formation of grain yield. A better understanding of the ecophysiological determinants of leaf N gradient at this phenological stage could consequently be crucial for improving wheat productivity and quality (Dreccer et al., 1998).