Zinc accumulation patterns in four Anthyllis vulneraria subspecies supplemented with mineral nitrogen or grown in the presence of their symbiotic bacteria

Aims

This work examines Zn accumulation in four Anthyllis vulneraria subspecies supplemented with mineral nitrogen or grown in the presence of their symbiotic bacteria.

Methods

Anthyllis vulneraria subspecies were grown hydroponically in the presence of high levels of ZnSO₄. The plants were either grown in symbiosis with one of two non-metallicolous or metallicolous Mesorhizobium inoculants or in the presence of KNO₃.

Results

When exposed to 1,000 μM Zn, shoot and root biomass of three out of our four Anthyllis subspecies cultivated with NO₃ dropped significantly by about 24–28 %; carpatica, the fourth subspecies, was not affected. Subspecies carpatica Zn tolerance was confirmed when in symbiosis with the metallicolous strain. In the presence of 1,000 μM Zn, the different Anthyllis subspecies concentrated more Zn in their roots than in their shoots and only subsp. carpatica accumulated a significant amount of Zn in its shoots. The most remarkable feature was the drastic decrease in Zn concentration in both roots (up to 2.5–3 fold) and shoots (2.6-fold) of subsp. carpatica exposed to 1,000 μM Zn and nodulated whatever the Mesorhizobium strain used, compared to the N-grown plants.

Conclusions

Our results bring new perspectives as regards phytostabilization, with the potential use of a rhizobium-inoculated leguminous subspecies displaying unusual Zn tolerance.     

Aluminum induces low phosphate adaptive responses and modulates primary and lateral root growth by differentially affecting auxin signaling in Arabidopsis seedlings

Aims

The aims of this work were to investigate the aluminum (Al) and phosphate (P) interactions in the regulation of root system architecture of Arabidopsis thaliana seedlings and the contribution of auxin signaling in primary and lateral root growth in response to Al toxicity.

Methods

Detailed analyses of root system architecture and cell division were performed in Arabidopsis WT seedlings and in low phosphorus insensitive mutants lpi1-3 and lpr1-1 lpr2-1 in response to Al. Expression studies of P-deficiency regulated phosphate transporter AtPT2 were also conducted. The role of auxin as a mediator of root morphogenetic changes by Al was evaluated by using the auxin-signaling mutants tir1, tir1 afb2 afb3, and arf7 arf19.

Results

Al inhibited primary root growth by affecting cell cycle progression and causing differentiation of cells in the root meristem. These effects were reduced in low phosphorus insensitive lpi1-3 and low phosphate resistant lpr1-1 lpr2-1 Arabidopsis mutants. Al also activated the expression of the low phosphate-induced P transporter AtPT2 in roots. Lateral root formation by Al decreased in tir1 afb2 afb3 while arf7 arf19 mutants were highly resistant to Al in both primary root inhibition and lateral root induction.

Conclusions

Our results suggest that lateral root formation in response to Al toxicity and P deficiency may involve common signaling mechanisms, while a pathway involving ARF7 and ARF19 is important for primary root growth inhibition by Al.     

Ecosystem changes in Galápagos highlands by the invasive tree Cinchona pubescens

Background and aims

Salinity is an increasing problem for agricultural production worldwide. Understanding how Na⁺ enters plants is important if reducing Na⁺ influx, a key component of the regulation of Na⁺ accumulation in plants and improving salt tolerance of crop plants, is to be achieved. Our previous work indicated that two distinct low-affinity Na⁺ uptake pathways exist in the halophyte Suaeda maritima. Here, we report the external NaCl concentration at which uptake switches from pathway 1 to pathway 2 and the kinetics of the interaction between external K⁺ concentration and Na⁺ uptake and accumulation in S. maritima in order to determine the roles of K⁺ transporters or channels in low-affinity Na⁺ uptake.

Methods

Na⁺ influx, Na⁺ and K⁺ accumulations in S. maritima exposed to various concentrations of NaCl (0–200 mM) were analyzed in the absence and presence of the inhibitors TEA and Ba⁺ (5 mM TEA or 3 mM Ba²⁺) or KCl (0, 10 or 50 mM).

Results

Our earlier proposal was confirmed and extended that there are two distinct low-affinity Na⁺ uptake pathways in S. maritima: pathway 1 might be mediated by a HKT-type transporter under low salinity conditions and pathway 2 by an AKT1-type channel or a KUP/HAK/KT type transporter under high salinity conditions. The external NaCl concentration at which two distinct low-affinity Na⁺ uptake switches from pathway 1 to pathway 2, the ‘turning point’, is between 90 and 95 mM. Over a short period (12 h) of Na⁺ and K⁺ treatments, a low concentration of K⁺ (10 mM) facilitated Na⁺ uptake by S. maritima under high salinity (100–200 mM NaCl), whether or not the plants had been subjected to a longer (3 d) period of K⁺ starvation. The kinetics suggests that low concentration of K⁺ (10 mM) might activate AKT1-type channels or KUP/HAK/KT-type transporters under high salinity (100–200 mM NaCl).

Conclusions

The turning-point of external NaCl concentrations for the two low-affinity Na⁺ uptake pathways in Suaeda maritima is between 90 and 95 mM. A low concentration of K⁺ (10 mM) might activate AKT1 or KUP/HAK/KT and facilitate Na⁺ uptake under high salinity (100–200 mM NaCl). The kinetics of K⁺ on Na⁺ uptake and accumulation in S maritima are also consistent with there being two low-affinity Na⁺ uptake pathways.     

Phosphate aggravates iron chlorosis in sensitive plants grown on model calcium carbonate−iron oxide systems

Background and aims

The possible influence of phosphorus (P) on iron (Fe) deficiency chlorosis in susceptible plants needs elucidation. In this work, we tested the hypothesis that Fe chlorosis can be aggravated at high levels of P in the substrate.

Methods

Chickpea, lupin and peanut (in a preliminary experiment), and lupin and sorghum (in a second, factorial experiment) were successively grown on artificial substrates consisting of mixtures of Fe oxide-coated sand (FOCS), calcium carbonate (calcite) sand (CCS) and quartz sand to which phosphate was added at different doses.

Results

The proportion of FOCS in the substrate had a significant positive effect on leaf chlorophyll concentration (as estimated via SPAD) in all crops. In the factorial experiment, the SPAD value was negatively affected by the proportion of CCS in the dicot (lupin) but not in the monocot (sorghum). In the preliminary experiment, increasing the P dose generally had little effect on the SPAD of plants grown on the FOCS-rich substrate but a negative effect on those grown on the FOCS-poor substrate. In the factorial experiment, the P dose negatively affected SPAD in both lupin and sorghum.

Conclusions

Iron acquisition by the plant is negatively influenced by P probably because the solubility of the Fe oxides decreases with increasing coverage of their surfaces by sorbed phosphate.     

Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale

Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants.     

Structural Determinants at the Interface of the ARC2 and Leucine-Rich Repeat Domains Control the Activation of the Plant Immune Receptors Rx1 and Gpa2

Many plant and animal immune receptors have a modular nucleotide-binding-leucine-rich repeat (NB-LRR) architecture in which a nucleotide-binding switch domain, NB-ARC, is tethered to a LRR sensor domain. The cooperation between the switch and sensor domains, which regulates the activation of these proteins, is poorly understood. Here, we report structural determinants governing the interaction between the NB-ARC and LRR in the highly homologous plant immune receptors Gpa2 and Rx1, which recognize the potato cyst nematode Globodera pallida and Potato virus X, respectively. Systematic shuffling of polymorphic sites between Gpa2 and Rx1 showed that a minimal region in the ARC2 and N-terminal repeats of the LRR domain coordinate the activation state of the protein. We identified two closely spaced amino acid residues in this region of the ARC2 (positions 401 and 403) that distinguish between autoactivation and effector-triggered activation. Furthermore, a highly acidic loop region in the ARC2 domain and basic patches in the N-terminal end of the LRR domain were demonstrated to be required for the physical interaction between the ARC2 and LRR. The NB-ARC and LRR domains dissociate upon effector-dependent activation, and the complementary-charged regions are predicted to mediate a fast reassociation, enabling multiple rounds of activation. Finally, we present a mechanistic model showing how the ARC2, NB, and N-terminal half of the LRR form a clamp, which regulates the dissociation and reassociation of the switch and sensor domains in NB-LRR proteins.Resistance (R) proteins play a central role in the recognition-based immune system of plants. Unlike vertebrates, plants lack an adaptive immune system with highly specialized immune cells. Instead, they rely on an innate immune system in which each cell is autonomous. Two types of immune receptors can be distinguished in plants, pathogen-associated molecular patterns recognition receptors that detect conserved molecular patterns in plant pathogens and intracellular R proteins that recognize specific effectors employed by pathogens as modifiers of host metabolism or defense mechanisms (Jones and Dangl, 2006). Effector-triggered activation of R proteins leads to an array of protective responses, often culminating in programmed cell death at the site of infection (Greenberg and Yao, 2004), thereby preventing further ingress of the pathogen. Pathogens have evolved mechanisms to evade recognition by R proteins and to regain their virulence (Dodds and Rathjen, 2010). This continuous coevolutionary process between host and pathogen has resulted in a reservoir of highly diverse R proteins in plants, enabling them to counteract a wide range of pathogens and pests.The most common class of R proteins consists of nucleotide-binding (NB)-leucine-rich repeat (LRR) proteins with a tripartite domain architecture, which roughly corresponds to an N-terminal response domain (a coiled coil [CC] or Toll/Interleukin-1 receptor [TIR] domain) involved in downstream signaling, a central molecular switch domain (the NB domain present in the mammalian apoptosis regulator Apaf1, plant R proteins, and the Caenorhabditis elegans apoptosis regulator CED4 [NB-ARC]), and a C-terminal sensor domain (the LRR domain). The NB-ARC domain is an extended nucleotide-binding domain that plant immune receptors share with metazoan apoptosis regulators and immune receptors such as Apaf1, CED4, and nucleotide-binding oligomerization domain (NOD-like) receptors (NLRs) and belongs to the STAND (signal transduction ATPases with numerous domains) family of nucleoside triphosphatase domains (van der Biezen and Jones, 1998; Leipe et al., 2004; Albrecht and Takken, 2006; Maekawa et al., 2011b). The overall modular architecture of metazoan STAND nucleoside triphosphatase is similar to that of NB-LRR plant immune receptors, but the domains flanking the NB-ARC domain often differ. In NLRs, for example, several N-terminal domains can be found, including caspase-recruiting domains and Pyrin domains (Proell et al., 2008). In the mammalian protein Apaf1, the sensor involved in cytochrome c detection consists of C-terminal WD40 repeats (Zou et al., 1997).In plant NB-LRR resistance proteins, the recognition of a pathogen effector via the LRR domain is thought to switch the conformation of the protein from a closed, autoinhibited “off” state into an open, active “on” state (Lukasik and Takken, 2009). The activation of NB-LRR proteins is most likely a multistep process in which the NB-ARC domain plays a central role. The three subdomains of the NB-ARC, the NB, ARC1, and ARC2, collectively form a nucleotide-binding pocket that adopts different conformations depending on the bound nucleotide. This mechanism seems to be conserved between proteins from organisms as distant as bacteria, metazoans, and plants (Rairdan and Moffett, 2007; Danot et al., 2009; Takken and Tameling, 2009). The conformational change coincides with the exchange of bound ADP for ATP in the NB-ARC, probably stabilizing the active conformation (Tameling et al., 2006; Ade et al., 2007). Hydrolysis of the bound ATP is hypothesized to return the domains to their inactive state. The exact mechanism by which elicitor recognition via the LRR leads to a conformational change of the NB-ARC and the subsequent activation of immune signaling pathways is not clear.Previous studies have shown that the CC/TIR, NB-ARC, and LRR domains in plant immune receptors interact and cooperate with each other in an interdependent manner (Moffett et al., 2002; Leister et al., 2005; Ade et al., 2007; Rairdan et al., 2008). From these data, a picture emerges in which the LRR domain is not only involved in pathogen recognition, but also plays a role in maintaining an autoinhibited resting state in the absence of pathogens via its interactions with the other domains (Bendahmane et al., 2002; Hwang and Williamson, 2003; Ade et al., 2007; Qi et al., 2012). A similar role as regulatory domain has been found for the sensor domains of other NLRs, such as the mammalian Apaf1 (Hu et al., 1998). For the potato (Solanum tuberosum) immune receptor Rx1, a model plant NB-LRR protein, it has been shown that the LRR cooperates with the ARC subdomains in retaining the inactive state of the protein. The deletion of the ARC and LRR domains leads to a constitutive activity of the NB (Bendahmane et al., 2002; Rairdan et al., 2008). In addition, it was demonstrated that the elicitor, the Potato virus X (PVX) coat protein, modifies the interdomain interactions in Rx1 (Moffett et al., 2002; Rairdan et al., 2008). Sequence exchanges between Rx1 and the highly homologous nematode resistance protein Gpa2 (88% amino acid identity) resulted in incompatibilities between the domains that give rise to inappropriate activation of cell death responses (Rairdan and Moffett, 2006), indicating that the cooperation between the sensor and switch domains depends on an interaction fine tuned by intramolecular coevolution. In this light, it is interesting to note that a functional ortholog of Rx1, Rx2 from Solanum acaule, is almost identical to Rx1 in its LRR region but displays a higher similarity to Gpa2 in stretches of its CC-NB-ARC sequence (Bendahmane et al., 2000).The aim of our study was to pinpoint the molecular determinants controlling the switch between the resting and activation state of NB-LRR proteins. The incompatibility between the ARC and LRR domains of Rx1 and Gpa2 was used as a guideline to dissect the molecular and structural determinants involved in the cooperation between the switch (NB-ARC) and sensor (LRR) domain. An extensive exchange of polymorphic residues between these two homologous NB-LRR proteins resulted in the identification of a minimal fragment of 68 amino acid residues in the ARC2 domain and the first LRR repeats as being crucial for proper activation of Gpa2 and Rx1. Within this minimal region, we identified two amino acids that, despite their proximity in the amino acid sequence, differentiate between elicitor-dependent (position 401) and independent activation (position 403). However, structural modeling of the domains shows that the residue at position 403 operates at the interface of the ARC2 and N-terminal part of the LRR domain, while residue 401 mapped at the interface between the ARC2 and NB domain. Furthermore, an acidic loop region in the ARC2 domain and complementary-charged basic patches in the N-terminal half of the LRR domain are shown to be required for the physical interaction between these domains. We demonstrate that the binding between the CC- NB-ARC and LRR domains is disrupted upon elicitor-dependent activation and that the complementary-charged residues are predicted to facilitate reassociation. Two independent docking simulations of the NB-ARC and LRR domain indicate that the LRR domain binds to the NB-ARC domain at the surface formed by the interaction of the ARC2 and NB subdomains. We present a mechanistic model in which the first repeats of the LRR, the ARC2 subdomain, and the NB form a clamp, which governs the shuttling between a closed, autoinhibited “off” state and an open, active “on” state of the resistance protein. Finally, we discuss the consequences of the functional constraints imposed by the interface of the NB, ARC2, and LRR domain for the generation of novel resistance specificities via evolutionary processes and genetic engineering.