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For the full activation of cyclin‐dependent kinases (CDKs), not only cyclin binding but also CDK phosphorylation is required. This activating phosphorylation is mediated by CDK‐activating kinases (CAKs). Arabidopsis has four genes showing similarity to vertebrate‐type CAKs, three CDKDs (CDKD;1CDKD;3) and one CDKF (CDKF;1). We previously found that the cdkf;1 mutant is defective in post‐embryonic development, even though the kinase activities of core CDKs remain unchanged relative to the wild type. This raised a question about the involvement of CDKDs in CDK activation in planta. Here we report that the cdkd;1 cdkd;3 double mutant showed gametophytic lethality. Most cdkd;1‐1 cdkd;3‐1 pollen grains were defective in pollen mitosis I and II, producing one‐cell or two‐cell pollen grains that lacked fertilization ability. We also found that the double knock‐out of CDKD;1 and CDKD;3 caused arrest and/or delay in the progression of female gametogenesis at multiple steps. Our genetic analyses revealed that the functions of CDKF;1 and CDKD;1 or CDKD;3 do not overlap, either during gametophyte and embryo development or in post‐embryonic development. Consistent with these analyses, CDKF;1 expression in the cdkd;1‐1 cdkd;3‐1 mutant could not rescue the gametophytic lethality. These results suggest that, in Arabidopsis, CDKD;1 and CDKD;3 function as CAKs controlling mitosis, whereas CDKF;1 plays a distinct role, mainly in post‐embryonic development. We propose that CDKD;1 and CDKD;3 phosphorylate and activate all core CDKs, CDKA, CDKB1 and CDKB2, thereby governing cell cycle progression throughout plant development.  相似文献   

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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.  相似文献   

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RNA silencing plays an important antiviral role in plants and invertebrates. To counteract antiviral RNA silencing, most plant viruses have evolved viral suppressors of RNA silencing (VSRs). TRIPLE GENE BLOCK PROTEIN1 (TGBp1) of potexviruses is a well-characterized VSR, but the detailed mechanism by which it suppresses RNA silencing remains unclear. We demonstrate that transgenic expression of TGBp1 of plantago asiatica mosaic virus (PlAMV) induced developmental abnormalities in Arabidopsis thaliana similar to those observed in mutants of SUPPRESSOR OF GENE SILENCING3 (SGS3) and RNA-DEPENDENT RNA POLYMERASE6 (RDR6) required for the trans-acting small interfering RNA synthesis pathway. PlAMV-TGBp1 inhibits SGS3/RDR6-dependent double-stranded RNA synthesis in the trans-acting small interfering RNA pathway. TGBp1 interacts with SGS3 and RDR6 and coaggregates with SGS3/RDR6 bodies, which are normally dispersed in the cytoplasm. In addition, TGBp1 forms homooligomers, whose formation coincides with TGBp1 aggregation with SGS3/RDR6 bodies. These results reveal the detailed molecular function of TGBp1 as a VSR and shed new light on the SGS3/RDR6-dependent double-stranded RNA synthesis pathway as another general target of VSRs.  相似文献   

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Plasma membrane-localized pattern recognition receptors such as FLAGELLIN SENSING2 (FLS2) and EF-TU RECEPTOR (EFR) recognize microbe-associated molecular patterns (MAMPs) to activate the first layer of plant immunity termed pattern-triggered immunity (PTI). A reverse genetics approach with genes responsive to the priming agent β-aminobutyric acid (BABA) revealed IMPAIRED OOMYCETE SUSCEPTIBILITY1 (IOS1) as a critical PTI player. Arabidopsis thaliana ios1 mutants were hypersusceptible to Pseudomonas syringae bacteria. Accordingly, ios1 mutants demonstrated defective PTI responses, notably delayed upregulation of PTI marker genes, lower callose deposition, and mitogen-activated protein kinase activities upon bacterial infection or MAMP treatment. Moreover, Arabidopsis lines overexpressing IOS1 were more resistant to P. syringae and demonstrated a primed PTI response. In vitro pull-down, bimolecular fluorescence complementation, coimmunoprecipitation, and mass spectrometry analyses supported the existence of complexes between the membrane-localized IOS1 and FLS2 and EFR. IOS1 also associated with BRASSINOSTEROID INSENSITIVE1-ASSOCIATED KINASE1 (BAK1) in a ligand-independent manner and positively regulated FLS2/BAK1 complex formation upon MAMP treatment. Finally, ios1 mutants were defective in BABA-induced resistance and priming. This work reveals IOS1 as a regulatory protein of FLS2- and EFR-mediated signaling that primes PTI activation upon bacterial elicitation.  相似文献   

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Myo-inositol-1,2,3,4,5,6-hexakisphosphate (InsP6), also known as phytic acid, accumulates in large quantities in plant seeds, serving as a phosphorus reservoir, but is an animal antinutrient and an important source of water pollution. Here, we report that Gle1 (GLFG lethal 1) in conjunction with InsP6 functions as an activator of the ATPase/RNA helicase LOS4 (low expression of osmotically responsive genes 4), which is involved in mRNA export in plants, supporting the Gle1-InsP6-Dbp5 (LOS4 homolog) paradigm proposed in yeast. Interestingly, plant Gle1 proteins have modifications in several key residues of the InsP6 binding pocket, which reduce the basicity of the surface charge. Arabidopsis thaliana Gle1 variants containing mutations that increase the basic charge of the InsP6 binding surface show increased sensitivity to InsP6 concentrations for the stimulation of LOS4 ATPase activity in vitro. Expression of the Gle1 variants with enhanced InsP6 sensitivity rescues the mRNA export defect of the ipk1 (inositol 1,3,4,5,6-pentakisphosphate 2-kinase) InsP6-deficient mutant and, furthermore, significantly improves vegetative growth, seed yield, and seed performance of the mutant. These results suggest that Gle1 is an important factor responsible for mediating InsP6 functions in plant growth and reproduction and that Gle1 variants with increased InsP6 sensitivity may be useful for engineering high-yielding low-phytate crops.  相似文献   

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The genus Oryza, which includes rice (Oryza sativa and Oryza glaberrima) and wild relatives, is a useful genus to study leaf properties in order to identify structural features that control CO2 access to chloroplasts, photosynthesis, water use efficiency, and drought tolerance. Traits, 26 structural and 17 functional, associated with photosynthesis and transpiration were quantified on 24 accessions (representatives of 17 species and eight genomes). Hypotheses of associations within, and between, structure, photosynthesis, and transpiration were tested. Two main clusters of positively interrelated leaf traits were identified: in the first cluster were structural features, leaf thickness (Thickleaf), mesophyll (M) cell surface area exposed to intercellular air space per unit of leaf surface area (Smes), and M cell size; a second group included functional traits, net photosynthetic rate, transpiration rate, M conductance to CO2 diffusion (gm), stomatal conductance to gas diffusion (gs), and the gm/gs ratio. While net photosynthetic rate was positively correlated with gm, neither was significantly linked with any individual structural traits. The results suggest that changes in gm depend on covariations of multiple leaf (Smes) and M cell (including cell wall thickness) structural traits. There was an inverse relationship between Thickleaf and transpiration rate and a significant positive association between Thickleaf and leaf transpiration efficiency. Interestingly, high gm together with high gm/gs and a low Smes/gm ratio (M resistance to CO2 diffusion per unit of cell surface area exposed to intercellular air space) appear to be ideal for supporting leaf photosynthesis while preserving water; in addition, thick M cell walls may be beneficial for plant drought tolerance.Leaves have evolved in different environments into a multitude of sizes and shapes, showing great variation in morphology and anatomy (Evans et al., 2004). However, all leaf typologies share common functions associated with chloroplasts, namely to intercept sunlight, take up CO2 and inorganic nitrogen, and perform photosynthesis as a primary process for growth and reproduction.Investigating relationships between leaf anatomy and photosynthetic features (CO2 fixation, which involves physical and biochemical processes and loss of water by transpiration) could lead to the identification of structural features for enhancing crop productivity and improve our understanding of plant evolution and adaptation (Evans et al., 2004).Stomata, through which CO2 and water vapor diffuse into and out of the leaf, are involved in the regulation and control of photosynthetic and transpiration responses (Jarvis and Morison, 1981; Farquhar and Sharkey, 1982). Besides stomata distribution patterns between the abaxial and adaxial lamina surfaces (Foster and Smith, 1986), stomatal density and size are leaf anatomical traits contributing to build the leaf stomatal conductance to gas diffusion (gs). This is calculated as the reciprocal of the stomatal resistances to gas diffusion; stomatal control results in a lower concentration of CO2 in the leaf mesophyll (M) intercellular air space (Ci) than in the atmosphere (Ca; Nobel, 2009).Leaf M architecture greatly contributes to the pattern of light attenuation profiles within the lamina (Terashima and Saeki, 1983; Woolley, 1983; Vogelmann et al., 1989; Evans, 1999; Terashima et al., 2011) and affects CO2 diffusion from the intercellular air space (IAS) to the chloroplast stroma. Therefore, it influences photosynthetic activity (Flexas et al., 2007, 2008) and can have effects on leaf hydrology and transpiration (Sack et al., 2003; Brodribb et al., 2010; Ocheltree et al., 2012). In addition, M architecture sets boundaries for leaf photosynthetic responses to changing environmental conditions (Nobel et al., 1975).Fortunately, several methodologies are currently available (Flexas et al., 2008; Pons et al., 2009) to determine M conductance to CO2 diffusion (gm), expressed per unit of leaf surface area. It is calculated as the reciprocal of the cumulated partial resistances exerted by leaf structural traits and biochemical processes from the substomatal cavities to photosynthetic sites (Evans et al., 2009; Nobel, 2009). The resistance to CO2 diffusion in the liquid phase is 4 orders of magnitude higher than in the gaseous phase (Nobel, 2009); therefore, the changes in CO2 concentration in the leaf gas phase are small in comparison with the changes in the liquid phase (Niinemets, 1999; Aalto and Juurola, 2002; Nobel, 2009). In the liquid phase, the resistance to CO2 transfer is built from contributions by the cell walls, the plasmalemma, cytoplasm, chloroplast membranes, and stroma (Tholen and Zhu, 2011; Tholen et al., 2012); in addition, it involves factors associated with the carboxylation reaction (Kiirats et al., 2002; Evans et al., 2009). Thus, the concentration of CO2 in the chloroplasts (Cc) is lower than Ci and can limit photosynthesis.At steady state, the relationships between the leaf net photosynthetic rate (A), the concentrations of CO2, and the stomatal conductance to CO2 diffusion (gs_CO2) and gm are modeled based on Fick’s first law of diffusion (Nobel, 2009) as:(1)where Ca, Ci, and Cc are as defined above (Flexas et al., 2008).The magnitude of gm has been found to correlate with certain leaf structural traits in some species, in particular with the M cell surface area exposed to IAS per (one side) unit of leaf surface area (Smes) and its extent covered by chloroplasts (Schl; Evans and Loreto, 2000; Slaton and Smith, 2002; Tholen et al., 2012). From a physical modeling perspective, increasing Smes provides more pathways acting in parallel for CO2 diffusion (to and from the chloroplasts) per unit of leaf surface area; thus, it tends to reduce the resistance to CO2 movement into the M cells and to increase gm (Evans et al., 2009; Nobel, 2009). A number of leaf structural traits affect Smes, including leaf thickness, cell density, cell volume and shape, and the fraction of the M cell walls in contact with the IAS (Terashima et al., 2001, 2011), and the degree they are linked to Smes can vary between species (Slaton and Smith, 2002; Terashima et al., 2006). In particular, the presence of lobes on M cells, which are prominent in some Oryza species, may contribute to gm through increasing Smes (Sage and Sage, 2009; Terashima et al., 2011; Tosens et al., 2012). The M cell wall can provide resistance in series for M CO2 diffusion (Nobel, 2009); thicker cell walls may increase resistance to CO2 movement into the M cells and decrease gm (Terashima et al., 2006, 2011; Evans et al., 2009).Other leaf traits, such as M porosity (the fraction of M volume occupied by air spaces [VolIAS]), has been shown to have a positive correlation with gm in some species (Peña-Rojas et al., 2005), but the association may be mediated by light availability (Slaton and Smith, 2002). Leaf thickness (Thickleaf) tends to be negatively linked to gm, and it may set an upper limit for the maximum gm, according to Terashima et al. (2006), Flexas et al. (2008), and Niinemets et al. (2009).With respect to leaf structural traits and water relations, Thickleaf may increase the apoplast path length (resistances in series; Nobel, 2009) in the extra-xylem M (Sack and Holbrook, 2006; Brodribb et al., 2007) for water to reach the evaporation sites, which could decrease the conductance of water through the M and lower the transpiration rate. Interestingly, while thicker M cell walls may reduce gm, they can enable the development of higher water potential gradients between the soil and leaves, which can be decisive for plant survival and longevity under drought conditions (Steppe et al., 2011).The purpose of this study was to provide insight into how the diversity of leaf structure relates to photosynthesis and transpiration among representative cultivated species and wild relatives in the genus Oryza. This includes, in particular, identifying leaf structural features associated with the diffusion of CO2 from the atmosphere to the chloroplasts, photosynthesis, transpiration efficiency (A/E), and drought tolerance. The genus consists of 10 genomic groups and is composed of approximately 24 species (the number depending on taxonomic preferences; Kellogg, 2009; Brar and Singh, 2011), including the cultivated species Oryza sativa and Oryza glaberrima. Oryza species are distributed around the world, and they exhibit a wide range of phenotypes, with annual versus perennial life cycles and sun- versus shade-adapted species (Vaughan, 1994; Vaughan et al., 2008; Brar and Singh, 2011; Jagadish et al., 2011). This diversity in the genus is an important resource, which is being studied to improve rice yield, especially under unfavorable environmental conditions. In particular, O. glaberrima, Oryza australiensis, and Oryza meridionalis are of interest as drought-tolerant species (Henry et al., 2010; Ndjiondjop et al., 2010; Scafaro et al., 2011, 2012), while Oryza coarctata is salt tolerant (Sengupta and Majumder, 2010). In this study, a total of 43 leaf functional and structural parameters were collected on 24 accessions corresponding to 17 species within eight genomes (Brar and Singh (2011). Life cycle is as follows: A = annual; B = biennial; P = poliennial. Habitat is as follows: S = shade; S-Sh = sun-shade.
GenomeSpeciesLife CycleHabitatAccessionNo.
AAO. barthiiASPI 590400*1
AAO. glaberrimaASPI 450430*2
AAO. glumaepatulaPSPI 527362*3
AAO. longistaminataPSIRGC 101207*4
AAO. longistaminataPSIRGC 1017545
AAO. meridionalisA/PSIRGC 93265*6
AAO. nivaraA/BSPI 590405*7
AAO. rufipogonPSPI 1046408
AAO. rufipogonSPI 590421*9
AAO. sativaASIR64*10
AAO. sativaASIR7211
BBO. punctataAS-ShIRGC 105690*12
BBCCO. minutaPS-ShIRGC 101141*13
CCO. officinalisPS-ShPI 59412*14
CCO. rhizomatisPSIRGC 10160915
CCO. rhizomatisPSIRGC 105950*16
CCDDO. altaPS-ShPI 590398*17
CCDDO. latifoliaPS-ShIRGC 100959*18
CCDDO. latifoliaPS-ShIRGC 10517319
EEO. australiensisPSIRGC 101397*20
EEO. australiensisPSIRGC 105277*21
EEO. australiensisPSIRGC 8652722
FFO. brachyanthaBSIRGC 101232*23
HHKKO. coarctataPSIRGC 104502*24
Open in a separate windowFor evaluating aspects of photosynthesis, the model in Equation 1 was considered, and all the listed functional variables, A, gs_CO2, (CaCi), gm, and (CiCc), were determined. In addition, among the leaf functional traits, the M resistance to CO2 diffusion per unit of cell surface area exposed to IAS (reciprocal of gm/Smes) was calculated as described by Evans et al. (2009): it represents the resistance to CO2 diffusion from IAS to chloroplasts in a liquid solution through cell wall and membranes (Nobel, 2009). Leaf transpiration rate (E), A/E, the intrinsic A/E (ratio between A and stomatal conductance to water vapor diffusion [gs_H2O]), gm/gs_CO2 (representing the coordination between gm and gs), and the carbon isotope composition of leaf biomass (δ13C; calculated as 13C/12C) were determined. The value of δ13C has been recognized as a potential indicator of leaf A/E: increased limitations on photosynthesis by decreased gs can lead to higher A/gs_H2O ratios and less discrimination against assimilation of 13CO2 (for review, see Farquhar et al., 1989); the leaf A/E may also be positively linked to the gm/gs ratio (Flexas et al., 2008, 2013; Barbour et al., 2010). With respect to leaf structure, the stomatal density, stomatal pore length, and indices of stomatal pore area on both lamina sides (according to Sack et al., 2003), the Thickleaf, VolIAS, Smes, Schl, area of M cell section (acell) in leaf cross sections, cell wall thickness (Thickcw), and M cell surface lobing (Lobcell) were the principal traits estimated. A statistical multivariate analysis (Child, 2006) was employed to identify clusters of highly interrelated leaf traits; trait-to-trait correlation analysis was carried out to further examine leaf structural, functional, and structural-functional relationships.The following are the main hypotheses examined in this study. (1) Leaf thickness will be associated with certain M structural features. (2) gm will be coordinated with M structural traits. (3) A will be correlated with gs, gm, and E. (4) Leaf structural traits will be involved in the relationship between A and E, which will affect leaf A/E. (5) The gm/gs ratio will be positively correlated with leaf A/E; associations with high Thickcw could have implications for plant drought tolerance.  相似文献   

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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 (LpOUT and LpIN, 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 [Vo], and hydraulic conductivity [Lp], respectively) than the PC method (25.4%, 22.0%, and 24.2%, respectively). Vo as determined from PC and PR tests was 1.1 to 2.7 nL and in the range of optically estimated Vo values of 1.5 to 4.9 nL. For the same cell, Vo and Lp estimates were significantly lower (about 15% and 30%, respectively) when determined by PC compared with PR. Both methods, however, showed significantly higher LpOUT than LpIN (LpOUT/LpIN ≅ 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 LpOUT/LpIN over a wide range of Lp 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 [Lp]) 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, Lp 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 Lp (LpIN) was higher than outflow Lp (LpOUT) in these cells, with LpOUT/LpIN of about 0.65 (Dainty, 1963). When using osmotic driving forces in algal cells, LpOUT/LpIN 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), LpOUT/LpIN 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 LpOUT/LpIN averaging from 1.2 to 1.4. Moore and Cosgrove (1991) used two contrasting hydrostatic methods to measure Lp in sugarcane (Saccharum spp.) stem cells: (1) the most commonly used pressure relaxation (PR) method, in which cell turgor pressure (Pcell) changes during the measurement, and (2) the more technically demanding pressure clamp (PC) method, in which Pcell is maintained constant. Consistent with other studies in higher plant cells, Moore and Cosgrove (1991) reported average LpOUT/LpIN 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 LpOUT/LpIN (based on reported half-time [T1/2]) of 1.08. In view of the contribution of proteins (e.g. aquaporins) to overall membrane Lp, 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 LpOUT/LpIN. Cosgrove and Steudle (1981) reported that a substantial (6-fold) and rapid (within 20 s) reduction in Lp 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 Lp as indicative of the Lp in situ, and Wan et al. (2004) reported that a reduction in Lp was associated with perturbations to Pcell on the order of 0.1 MPa. Hence, if measured membrane Lp itself can exhibit substantial changes over relatively short periods of time in the same cell, then further study of systematic differences between LpOUT and LpIN 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 T1/2 of water exchange is measured by fitting an exponential curve to the observed decay in Pcell over time following a step change in volume, and membrane Lp can be calculated if cell surface area (A), cell volume (Vo), and volumetric elastic modulus (ε) are known (Steudle, 1993). In practice, A and Vo are typically calculated from optical measurements of individual cell dimensions or estimates using average values, and ε is calculated based on Vo 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), Vo (and, given reasonable assumptions about cell geometry, A) is estimated without the need for optical measurements, and Lp 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 (Kh) 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 (Poil) are recorded frequently (typically at 10 Hz), and Poil 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 Kh 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 LpOUT to LpIN in these cells.  相似文献   

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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 (JATP; 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 (JATP/GA). Using the metabolic model, measured JATP/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 (CBS), 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 (ATPBS + ATPM) for gross CO2 assimilation (GA; [ATPBS + ATPM]/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
AbbreviationDefinitionUnit
ANet assimilationμmol m−2 s−1
ABAbsorbed light
AB BS/MPartitioning of absorbed lightDimensionless
ATPBSATP demand in BSμmol m−2 s−1
ATPMATP demand in Mμmol m−2 s−1
BSBundle sheath
CBSCO2 concentration in BSμmol mol−1
CCMCarbon-concentrating mechanism
CEFCyclic electron flow
DHAPDihydroxyacetone phosphate
ETRElectron transport rateμmol m−2 s−1
GAGross assimilation (A + RLIGHT)μmol m−2 s−1
gBSBundle sheath conductance to CO2, calculated by fitting JMOD to JATPmol m2 s−1
IRGAInfrared gas analyzer
JATPTotal ATP production rateμmol m−2 s−1
JATPBSATP production rate in BSμmol m−2 s−1
JATPMATP production rate in Mμmol m−2 s−1
JMODModeled ATP production rateμmol m−2 s−1
LEFLinear electron flow
LCPLight compensation point
MMesophyll
MALMalate
MDHMalate dehydrogenase
MDHBSMalate dehydrogenase reaction rate in BSμmol m−2 s−1
MDHMMalate dehydrogenase reaction rate in Mμmol m−2 s−1
MEMalic enzyme
MEMalic enzyme reaction rateμmol m−2 s−1
NADPHBSNADPH demand in BSμmol m−2 s−1
NADPHTOTTotal NADPH demandμmol m−2 s−1
OAAOxaloacetic acid
PARPhotosynthetically active radiationμE m−2 s−1
PEPPhosphoenolpyruvate
PEPCKPhosphoenolpyruvate carboxykinase
PEPCKPEPCK reaction rateμmol m−2 s−1
PGA3-Phosphoglyceric acid
PPDKPyruvate phosphate dikinase
PPDKPPDK reaction rateμmol m−2 s−1
PRPGA reduction
PRBSPR rate in BSμmol m−2 s−1
PRMPR rate in Mμmol m−2 s−1
RBSRespiration in the light in BSμmol m−2 s−1
RLIGHTRespiration in the lightμmol m−2 s−1
RPPReductive pentose phosphate
RuBPRibulose-1,5-bisphosphate
RuPRibulose-5-phosphate
SSStarch synthesis
SSBSStarch synthesis rate in BSμmol m−2 s−1
SSMStarch synthesis rate in Mμmol m−2 s−1
SSTOTTotal starch synthesis rateμmol m−2 s−1
TTransamination rateμmol m−2 s−1
VCRubisco carboxylation rateμmol m−2 s−1
VORubisco oxygenation rateμmol m−2 s−1
VPPEP carboxylation rateμmol m−2 s−1
Y(II)Yield of PSII
Δ13C isotopic discrimination
δ13C13C isotopic composition relative to Pee Dee Belemnite
ΦLeakinessDimensionless
Open in a separate windowRecently, the maize C4 subgroup has been shown to be complicated by the presence of two BS decarboxylation enzyme systems (NADP-ME and phosphoenolpyruvate carboxykinase [PEPCK]), presumably both acting as CO2 delivery pathways (via malate [MAL] and Asp, respectively; Furumoto et al., 1999, 2000; Wingler et al., 1999; Eprintsev et al., 2011; Furbank, 2011; Pick et al., 2011). There is also an extensive overlap between BS and M functions, since both cell types can synthesize starch (Spilatro and Preiss, 1987; Kanai and Edwards, 1999) and reduce phosphoglyceric acid (PGA; Majeran and van Wijk, 2009; see the overall scheme in Fig. 1). Additionally, energetic partitioning can also vary between cell types, since the total ATP produced (JATP) per CO2 fixed in GA (JATP/GA) may be produced in BS (mainly through cyclic electron flow [CEF] around PSI) or in M (mainly through linear electron flow [LEF]), depending on the light locally available in BS or M (Kramer and Evans, 2011; Yin and Struik, 2012). Furthermore, although all NADPH is produced in M, the only compartment operating linear electron transport and oxidizing water, some NADPH is exported to BS through MAL diffusion, to meet the reducing power demand therein (NADPHBS). To capture the complex C4 physiology, several models of C4 photosynthesis have been developed (Berry and Farquhar, 1978; Laisk and Edwards, 2000, 2009; von Caemmerer, 2000). The earlier approaches were developed into the von Caemmerer (2000) C4 model. In particular, the associated light-limited equations (referred to subsequently as the “C4 model”) are used to estimate the parameters needed to resolve the isotopic discrimination (Δ) model, widely employed to study Φ under low-light conditions (for review, see Ubierna et al., 2011). The C4 model partitions JATP into two fractions: (1) the ATP consumed by PEP carboxylase, and (2) the ATP consumed by the C3 activity (glyoxylate recycling, PGA reduction [PR], and ribulose 1,5-bisphosphate [RuBP] regeneration). These activities are located in M, BS, or both compartments (see the overall scheme in Fig. 1). However, the C4 model simplifies the spatial compartmentalization between BS and M, and in this paper, we now develop the energetic implications of the differential contribution of M and BS to C4 photosynthesis under different light regimes.Open in a separate windowFigure 1.Metabolic model of C4 assimilation, rates of reaction, and net fluxes between BS and M. The overall scheme reports the reactions of the CCM (Furbank, 2011), Rubisco carboxylation, the reactions of the RPP pathway, the synthesis of starch, respiration, and glyoxylate recycling reactions. The tables, with the corresponding enzyme names, show the actual reaction rates, expressed relative to GA (5.13 μmol m−2 s−1), per unit of substrate transformed. Rates were estimated by parameterizing the model equations (PAR = 125 μE m−2 s−1 (A = 3.96 μmol m−2 s−1; RLIGHT = 1.17 μmol m−2 s−1; JATP = 28.6 μmol m−2 s−1), the output of the C4 model (VC = 5.35 μmol m−2 s−1; VP = 5.89 μmol m−2 s−1; VO = 0.44 μmol m−2 s−1), and the output of the Δ model (Φ = 0.23) under three characteristic ratios of ATP partitionings. These were numbered 1, 2, and 3. Condition 1 corresponds to the lowest ATP available in BS (ATP partitioning similar to that under blue light; Fig. 4B), condition 2 corresponds to an intermediate ATP availability in BS (ATP partitioning equal to that under red light; Fig. 4B), and condition 3 corresponds to the highest ATP available in BS (ATP partitioning equal to that under green light; Fig. 4B). The inset shows net metabolite fluxes between M and BS in multiples of GA. The ATP demand in BS (ATPBS) and M (ATPM), the total NADPH demand (NADPHTOT), and the NADPHBS were also calculated in the same three relevant conditions. PYR, Pyruvic acid.Because of these anatomical, metabolic, and energetic complexities, C4 metabolism is highly sensitive to limiting light intensity (Bellasio and Griffiths, 2013) and, potentially, light quality (Evans et al., 2007). Light quality has a greater influence on C4 photosynthesis than on C3. Leaf pigments preferentially absorb the blue and red region of the spectra, and some wavelengths penetrate deeper into leaves. It was shown in C3 leaves that exposure to different wavelengths results in characteristic light penetration profiles, which, translated into different gradients in PSII yield, rates of ATP production, and assimilation (A) within the leaf (Terashima et al., 2009). In C4 leaves, because of the concentric anatomy, light reaches M cells before the deeper BS (Evans et al., 2007) and could alter the balance between light harvesting and energetic partitioning between BS and M.In this paper, we model the likely profiles of light penetration for specific wavelengths associated with red, green, and blue light within a maize M and BS leaf cross section and calculate the impact on potential ATP production for each cell type. We calculate the proportion of absorbed light (AB) for each wavelength, expressed as AB BS/M, the fraction of photons absorbed in BS relative to the photons absorbed in M, from which we derive JATPBS/JATPM, the fraction of ATP produced in BS relative to the ATP produced in M. Second, we developed a steady-state metabolic model (Fig. 1; von Caemmerer 2000), to capture the spatial separation between BS and M and partitions the ATP demand between BS and M cells in terms of PR, starch synthesis (SS), and PEP regeneration, so as to meet the ATP availability in each cell type (Evans et al., 2007). Third, photosynthetic characteristics (leaf-level ATP production rate, CO2 assimilation, stomatal conductance, and Φ derived from online carbon isotope discrimination [Δ]) were measured under red, green, and blue light, and red, green, and blue light in combination (RGB), using a decreasing photon flux density (from 500 to 50 μE m−2 s−1) to investigate the importance of metabolic plasticity under limiting light intensities.

Table II.

Steady-state equations for the metabolic model of C4 assimilationProcesses described by Equations 4 to 10 can be calculated directly from the measured data for A, RLIGHT, and the output of the von Caemmerer C4 model (VO, VP, and VC), while Equations 11 to 21 require prior allocation of SS, PR, and PEPCK. For simplicity, enzyme names in italics represent the enzyme reaction rate. For stoichiometric consistency, reaction rates are calculated as rates of substrate transformation.
ProcessSymbolReaction RateEquationLocalizationNotes
Gross assimilationGA(4)GA and RLIGHT rates are expressed per CO2.
RuP phosphorylation(5)BSRuP phosphorylation supplies Rubisco carboxylating activity (VC) together with oxygenating activity (VO).
Total PRPRTOT(6)BS and MThis equation calculates the total rate of PR on the basis of the PGA produced by Rubisco carboxylation (2VC), Rubisco oxygenation (VO), and glyoxylate recycling (0.5VO) and considers the PGA consumed by respiration; 1/3 is the stoichiometric conversion between respiration (expressed per CO2) and PR (expressed per triose).
Total NADPH demandNADPHTOT(7)BS and MPR consumes one NADPH per PGA; the total rate of PR is PRTOT (see note to Eq. 6); in glyoxylate regeneration (per glyoxylate), 0.5 NADH is produced by Gly decarboxylase, 0.5 NADH is consumed by hydroxypyruvate reductase, and one ferredoxin (equivalent to 0.5 NADPH) is consumed by Gln synthetase; in total, 0.5 NADPH is consumed per glyoxylate (equivalent to VO rate; Supplemental Table S1; Yoshimura et al., 2004).
DHAP entering RPP(8)BSThe DHAP entering the RPP pathway corresponds to the total PR rate minus the DHAP used for starch synthesis, which in this work is expressed per triose.
Total SSSSTOT(9)BS and MIn this model, assimilation is entirely converted to starch; this assumption does not influence energetics, as starch synthesis has the same ATP demand as phloem-loaded Suc; in Equation 9, 1/3 converts the stoichiometry of A (expressed per CO2) to the stoichiometry of SS (expressed per triose).
Total PEP regeneration(10)BS and MPEP regeneration rate equals PEP consumption rate VP at steady state; PEP can be regenerated either by PPDK (mainly in M but active also in BS) or by PEPCK in BS; in this study, PPDK activity was assumed to be zero in BS.
Total ATP demandATPBS + ATPM(11)BS and MEquation 11 calculates the total ATP demand as the sum of ATP demand for PR (one ATP per PGA, corresponding to PR), RuBP regeneration (one ATP per RuP, corresponding to VC + VO), glyoxylate recycling (one ATP per glyoxylate, corresponding to VO), starch synthesis (0.5 ATP per triose, corresponding to SS), and PEP regeneration (one ATP per PEPCK catalytic event or two ATP per PPDK catalytic event); compared with the original formulation of the C4 model, Equation 11 separates the ATP demand for PEPCK and PPDK, includes the ATP demand for SS, and considers the PGA utilized by respiration, which does not need to be reduced (see Eq. 6).
ATP demand in BSATPBS(12)BSThe ATP demand in BS is brought about by PR (at the rate of PRBS), RuBP regeneration (at the rate of VC + VO), glyoxylate recycling (at the rate of VO), starch synthesis (0.5 ATP per triose), and PEPCK activity (one ATP per OAA; see note to Eq. 11).
ATP demand in MATPM(13)MThe ATP demand in M is brought about by PR (at the rate of PRM), SS, and PPDK (two ATPs per pyruvic acid; see note to Eq. 11).
NADPH demand in BSNADPHBS(14)BSThe NADPH demand in BS is brought about by PR (one NADPH per PGA) and glyoxylate recycling, which consumes 0.5 NADPH per glyoxylate (corresponding to VO; see Supplemental Table S2).
NADPH supply to BSMDHM(15)BSAll NADPH available in BS is produced in M and exported through the MAL shuttle because we have assumed that no linear electron transport (i.e. water oxidation) occurred in BS; for this reason, the NADPH supply to BS corresponds to the NADPH consumed to reduce OAA to MAL in M, the process responsible for NADPH export, and not to the rate of MAL decarboxylation in BS, which depends on T, PEPCK, and MDHBS (Eq. 19).
MDH activity in MMDHM(16)MMDH activity supplies the NADPH demand in BS; Equation 16 was derived from Equations 14 and 15.
TransaminationT(17)BS and MEquation 17 expresses that, at steady state, all OAA is either transaminated or reduced; since T bypasses the MDHM reaction, which is the reaction responsible for NADPH export to BS (see note to Eq. 15), T has the function of balancing NADPH supply and demand, which becomes apparent when Equations 15 and 17 are combined.
MDHMDHBST − PEPCK(18)BSMDH is assumed to operate a fast conversion at equilibrium; therefore, it is passively regulated by the substrate availability: the OAA that is not used by PEPCK is reduced to MAL by MDH; MDH may use NADH, since no NADPH-dependent reduction of OAA has been observed in maize (Kanai and Edwards, 1999) and it is likely mitochondrial (Rathnam, 1978; Chapman and Hatch, 1981); the NADH regeneration may be carried out by chloroplastic ME, which is reported to react both with NADP and NAD (Chapman and Hatch, 1981); however, the process may be more complicated (Eprintsev et al., 2011, and refs. therein); note that in this study, we assumed that cells are decompartmentalized while PEPCK rate was manipulated to increase between zero and a maximum rate in response to ATP availability (see “Minimum and Maximum BS Allocation” for details).
MEMEMDHM + MDHBS19BSEquation 19 expresses that the rate of MAL oxidation by ME corresponds to the rate of MAL produced by MDH activity in M plus the rate of MAL produced by MDH activity in BS.
PPDKPPDKVP − PEPCK20MThe PEP regenerated by PEPCK in BS diffuses to M and reduces the requirement of PEP regenerated by PPDK in M.
PR in MPRMPRTOT − PRBS21MPR is a shared process between BS and M.
Open in a separate windowFor instance, AB BS/M and JATPBS/JATPM were both lower under the blue light (wavelength 460 nm), which is rapidly extinguished within the M leaf profile, than under white light, confirming that light quality perturbs C4 energetics. In spite of this shift, when maize plants were exposed to different light qualities, there was no change in Φ, indicating that, at steady state, the coordination between CCM activity and Rubisco assimilation was retained (Ubierna et al., 2011; Sun et al., 2012). The modeled metabolic plasticity projected a window for ATP demand partitioning (ATPBS/ATPM), which matched the values for JATPBS/JATPM supply estimated under red, green, and blue light. We show that the plasticity of C4 metabolism, and in particular the possibility of shifting between MAL and Asp as a primary carboxylase product, was of pivotal importance in allowing the plasticity of ATP and NADPH demand. In conclusion, our study explains the extensive overlap between BS and M functions and the requirement for at least two decarboxylase systems in NADP-ME subtype plants such as maize, providing an explanation for empirical observations on the diversity of decarboxylase activities and PEP regeneration pathways (Rathnam, 1978; Chapman and Hatch, 1981; Wingler et al., 1999; Eprintsev et al., 2011; Furbank, 2011; Pick et al., 2011).  相似文献   

19.
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.  相似文献   

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