Spore Density Determines Infection Strategy by the Plant Pathogenic Fungus Plectosphaerella cucumerina

Necrotrophic and biotrophic pathogens are resisted by different plant defenses. While necrotrophic pathogens are sensitive to jasmonic acid (JA)-dependent resistance, biotrophic pathogens are resisted by salicylic acid (SA)- and reactive oxygen species (ROS)-dependent resistance. Although many pathogens switch from biotrophy to necrotrophy during infection, little is known about the signals triggering this transition. This study is based on the observation that the early colonization pattern and symptom development by the ascomycete pathogen Plectosphaerella cucumerina (P. cucumerina) vary between inoculation methods. Using the Arabidopsis (Arabidopsis thaliana) defense response as a proxy for infection strategy, we examined whether P. cucumerina alternates between hemibiotrophic and necrotrophic lifestyles, depending on initial spore density and distribution on the leaf surface. Untargeted metabolome analysis revealed profound differences in metabolic defense signatures upon different inoculation methods. Quantification of JA and SA, marker gene expression, and cell death confirmed that infection from high spore densities activates JA-dependent defenses with excessive cell death, while infection from low spore densities induces SA-dependent defenses with lower levels of cell death. Phenotyping of Arabidopsis mutants in JA, SA, and ROS signaling confirmed that P. cucumerina is differentially resisted by JA- and SA/ROS-dependent defenses, depending on initial spore density and distribution on the leaf. Furthermore, in situ staining for early callose deposition at the infection sites revealed that necrotrophy by P. cucumerina is associated with elevated host defense. We conclude that P. cucumerina adapts to early-acting plant defenses by switching from a hemibiotrophic to a necrotrophic infection program, thereby gaining an advantage of immunity-related cell death in the host.Plant pathogens are often classified as necrotrophic or biotrophic, depending on their infection strategy (Glazebrook, 2005; Nishimura and Dangl, 2010). Necrotrophic pathogens kill living host cells and use the decayed plant tissue as a substrate to colonize the plant, whereas biotrophic pathogens parasitize living plant cells by employing effector molecules that suppress the host immune system (Pel and Pieterse, 2013). Despite this binary classification, the majority of pathogenic microbes employ a hemibiotrophic infection strategy, which is characterized by an initial biotrophic phase followed by a necrotrophic infection strategy at later stages of infection (Perfect and Green, 2001). The pathogenic fungi Magnaporthe grisea, Sclerotinia sclerotiorum, and Mycosphaerella graminicola, the oomycete Phytophthora infestans, and the bacterial pathogen Pseudomonas syringae are examples of hemibiotrophic plant pathogens (Perfect and Green, 2001; Koeck et al., 2011; van Kan et al., 2014; Kabbage et al., 2015).Despite considerable progress in our understanding of plant resistance to necrotrophic and biotrophic pathogens (Glazebrook, 2005; Mengiste, 2012; Lai and Mengiste, 2013), recent debate highlights the dynamic and complex interplay between plant-pathogenic microbes and their hosts, which is raising concerns about the use of infection strategies as a static tool to classify plant pathogens. For instance, the fungal genus Botrytis is often labeled as an archetypal necrotroph, even though there is evidence that it can behave as an endophytic fungus with a biotrophic lifestyle (van Kan et al., 2014). The rice blast fungus Magnaporthe oryzae, which is often classified as a hemibiotrophic leaf pathogen (Perfect and Green, 2001; Koeck et al., 2011), can adopt a purely biotrophic lifestyle when infecting root tissues (Marcel et al., 2010). It remains unclear which signals are responsible for the switch from biotrophy to necrotrophy and whether these signals rely solely on the physiological state of the pathogen, or whether host-derived signals play a role as well (Kabbage et al., 2015).The plant hormones salicylic acid (SA) and jasmonic acid (JA) play a central role in the activation of plant defenses (Glazebrook, 2005; Pieterse et al., 2009, 2012). The first evidence that biotrophic and necrotrophic pathogens are resisted by different immune responses came from Thomma et al. (1998), who demonstrated that Arabidopsis (Arabidopsis thaliana) genotypes impaired in SA signaling show enhanced susceptibility to the biotrophic pathogen Hyaloperonospora arabidopsidis (formerly known as Peronospora parastitica), while JA-insensitive genotypes were more susceptible to the necrotrophic fungus Alternaria brassicicola. In subsequent years, the differential effectiveness of SA- and JA-dependent defense mechanisms has been confirmed in different plant-pathogen interactions, while additional plant hormones, such as ethylene, abscisic acid (ABA), auxins, and cytokinins, have emerged as regulators of SA- and JA-dependent defenses (Bari and Jones, 2009; Cao et al., 2011; Pieterse et al., 2012). Moreover, SA- and JA-dependent defense pathways have been shown to act antagonistically on each other, which allows plants to prioritize an appropriate defense response to attack by biotrophic pathogens, necrotrophic pathogens, or herbivores (Koornneef and Pieterse, 2008; Pieterse et al., 2009; Verhage et al., 2010).In addition to plant hormones, reactive oxygen species (ROS) play an important regulatory role in plant defenses (Torres et al., 2006; Lehmann et al., 2015). Within minutes after the perception of pathogen-associated molecular patterns, NADPH oxidases and apoplastic peroxidases generate early ROS bursts (Torres et al., 2002; Daudi et al., 2012; O’Brien et al., 2012), which activate downstream defense signaling cascades (Apel and Hirt, 2004; Torres et al., 2006; Miller et al., 2009; Mittler et al., 2011; Lehmann et al., 2015). ROS play an important regulatory role in the deposition of callose (Luna et al., 2011; Pastor et al., 2013) and can also stimulate SA-dependent defenses (Chaouch et al., 2010; Yun and Chen, 2011; Wang et al., 2014; Mammarella et al., 2015). However, the spread of SA-induced apoptosis during hyperstimulation of the plant immune system is contained by the ROS-generating NADPH oxidase RBOHD (Torres et al., 2005), presumably to allow for the sufficient generation of SA-dependent defense signals from living cells that are adjacent to apoptotic cells. Nitric oxide (NO) plays an additional role in the regulation of SA/ROS-dependent defense (Trapet et al., 2015). This gaseous molecule can stimulate ROS production and cell death in the absence of SA while preventing excessive ROS production at high cellular SA levels via S-nitrosylation of RBOHD (Yun et al., 2011). Recently, it was shown that pathogen-induced accumulation of NO and ROS promotes the production of azelaic acid, a lipid derivative that primes distal plants for SA-dependent defenses (Wang et al., 2014). Hence, NO, ROS, and SA are intertwined in a complex regulatory network to mount local and systemic resistance against biotrophic pathogens. Interestingly, pathogens with a necrotrophic lifestyle can benefit from ROS/SA-dependent defenses and associated cell death (Govrin and Levine, 2000). For instance, Kabbage et al. (2013) demonstrated that S. sclerotiorum utilizes oxalic acid to repress oxidative defense signaling during initial biotrophic colonization, but it stimulates apoptosis at later stages to advance necrotrophic colonization. Moreover, SA-induced repression of JA-dependent resistance not only benefits necrotrophic pathogens but also hemibiotrophic pathogens after having switched from biotrophy to necrotrophy (Glazebrook, 2005; Pieterse et al., 2009, 2012).Plectosphaerella cucumerina ((P. cucumerina, anamorph Plectosporum tabacinum) anamorph Plectosporum tabacinum) is a filamentous ascomycete fungus that can survive saprophytically in soil by decomposing plant material (Palm et al., 1995). The fungus can cause sudden death and blight disease in a variety of crops (Chen et al., 1999; Harrington et al., 2000). Because P. cucumerina can infect Arabidopsis leaves, the P. cucumerina-Arabidopsis interaction has emerged as a popular model system in which to study plant defense reactions to necrotrophic fungi (Berrocal-Lobo et al., 2002; Ton and Mauch-Mani, 2004; Carlucci et al., 2012; Ramos et al., 2013). Various studies have shown that Arabidopsis deploys a wide range of inducible defense strategies against P. cucumerina, including JA-, SA-, ABA-, and auxin-dependent defenses, glucosinolates (Tierens et al., 2001; Sánchez-Vallet et al., 2010; Gamir et al., 2014; Pastor et al., 2014), callose deposition (García-Andrade et al., 2011; Gamir et al., 2012, 2014; Sánchez-Vallet et al., 2012), and ROS (Tierens et al., 2002; Sánchez-Vallet et al., 2010; Barna et al., 2012; Gamir et al., 2012, 2014; Pastor et al., 2014). Recent metabolomics studies have revealed large-scale metabolic changes in P. cucumerina-infected Arabidopsis, presumably to mobilize chemical defenses (Sánchez-Vallet et al., 2010; Gamir et al., 2014; Pastor et al., 2014). Furthermore, various chemical agents have been reported to induce resistance against P. cucumerina. These chemicals include β-amino-butyric acid, which primes callose deposition and SA-dependent defenses, benzothiadiazole (BTH or Bion; Görlach et al., 1996; Ton and Mauch-Mani, 2004), which activates SA-related defenses (Lawton et al., 1996; Ton and Mauch-Mani, 2004; Gamir et al., 2014; Luna et al., 2014), JA (Ton and Mauch-Mani, 2004), and ABA, which primes ROS and callose deposition (Ton and Mauch-Mani, 2004; Pastor et al., 2013). However, among all these studies, there is increasing controversy about the exact signaling pathways and defense responses contributing to plant resistance against P. cucumerina. While it is clear that JA and ethylene contribute to basal resistance against the fungus, the exact roles of SA, ABA, and ROS in P. cucumerina resistance vary between studies (Thomma et al., 1998; Ton and Mauch-Mani, 2004; Sánchez-Vallet et al., 2012; Gamir et al., 2014).This study is based on the observation that the disease phenotype during P. cucumerina infection differs according to the inoculation method used. We provide evidence that the fungus follows a hemibiotrophic infection strategy when infecting from relatively low spore densities on the leaf surface. By contrast, when challenged by localized host defense to relatively high spore densities, the fungus switches to a necrotrophic infection program. Our study has uncovered a novel strategy by which plant-pathogenic fungi can take advantage of the early immune response in the host plant.     

Grain setting defect1, Encoding a Remorin Protein,Affects the Grain Setting in Rice through Regulating Plasmodesmatal Conductance

Effective grain filling is one of the key determinants of grain setting in rice (Oryza sativa). Grain setting defect1 (GSD1), which encodes a putative remorin protein, was found to affect grain setting in rice. Investigation of the phenotype of a transfer DNA insertion mutant (gsd1-Dominant) with enhanced GSD1 expression revealed abnormalities including a reduced grain setting rate, accumulation of carbohydrates in leaves, and lower soluble sugar content in the phloem exudates. GSD1 was found to be specifically expressed in the plasma membrane and plasmodesmata (PD) of phloem companion cells. Experimental evidence suggests that the phenotype of the gsd1-Dominant mutant is caused by defects in the grain-filling process as a result of the impaired transport of carbohydrates from the photosynthetic site to the phloem. GSD1 functioned in affecting PD conductance by interacting with rice ACTIN1 in association with the PD callose binding protein1. Together, our results suggest that GSD1 may play a role in regulating photoassimilate translocation through the symplastic pathway to impact grain setting in rice.Grain filling, a key determinant of grain yield in rice (Oryza sativa), hinges on the successful translocation of photoassimilates from the leaves to the fertilized reproductive organs through the phloem transport system. Symplastic phloem loading, which is one of the main pathways responsible for the transport of photoassimilates in rice, is mediated by plasmodesmata (PD) that connect phloem companion cells with sieve elements and surrounding parenchyma cells (Kaneko et al., 1980; Chonan et al., 1981; Eom et al., 2012). PD are transverse cell wall channels structured with the cytoplasmic sleeve and the modified endoplasmic reticulum desmotubule between neighboring cells (Maule, 2008). A number of proteins affect the structure and functional performance of the PD, which in turn impacts the cell-to-cell transport of small and large molecules through the PD during plant growth, development, and defense (Cilia and Jackson, 2004; Sagi et al., 2005; Lucas et al., 2009; Simpson et al., 2009; Stonebloom et al., 2009). For example, actin and myosin, which link the desmotubule to the plasma membrane (PM) at the neck region of PD, are believed to play a role in regulating PD permeability by controlling PD aperture (White et al., 1994; Ding et al., 1996; Reichelt et al., 1999). Callose deposition can also impact the size of the PD aperture at the neck region (Radford et al., 1998; Levy et al., 2007) and callose synthase genes such as Glucan Synthase-Like7 (GSL7, also named CalS7), GSL8, and GSL12 have been shown to play a role in regulating symplastic trafficking (Guseman et al., 2010; Barratt et al., 2011; Vatén et al., 2011; Xie et al., 2011). Other proteins that have been shown to impact the structure and function of the PD include glycosylphosphatidylinositol (GPI)-anchored proteins, PD callose binding protein1 (PDCB1), which is also associated with callose deposition (Simpson et al., 2009), and LYSIN MOTIF DOMAIN-CONTAINING GLYCOSYLPHOSPHATIDYLINOSITOL-ANCHORED PROTEIN2, which limits the molecular flux through the PD by chitin perception (Faulkner et al., 2013). Changes in PD permeability can have major consequences for the translocation of photoassimilates needed for grain filling in rice. However, the genes and molecular mechanisms underlying the symplastic transport of photoassimilates remain poorly characterized.Remorins are a diverse family of plant-specific proteins with conserved C-terminal sequences and highly variable N-terminal sequences. Remorins can be classified into six distinct phylogenetic groups (Raffaele et al., 2007). The functions of most remorins are unknown, but some members of the family have been shown to be involved in immune response through controlling the cell-to-cell spread of microbes. StREM1.3, a remorin that is located in PM rafts and the PD, was shown to impair the cell-to-cell movement of a plant virus X by binding to Triple Gene Block protein1 (Raffaele et al., 2009). Medicago truncatula symbiotic remorin1 (MtSYMREM1), a remorin located at the PM in Medicago truncatula, was shown to facilitate infection and the release of rhizobial bacteria into the host cytoplasm (Lefebvre et al., 2010). Overexpression of LjSYMREM1, the ortholog of MtSYMREM1 in Lotus japonicus, resulted in increased root nodulation (Lefebvre et al., 2010; Tóth et al., 2012). Although a potential association between remorins and PD permeability has been proposed (Raffaele et al., 2009), the diversity observed across remorins, plus the fact that remorin mutants generated through different approaches fail to show obvious phenotypes (Reymond et al., 1996; Bariola et al., 2004), have made it challenging to characterize the function of remorins in cell-to-cell transport.In this study, we identified a rice transfer DNA (T-DNA) insertion mutant (grain setting defect1-Dominant [gsd1-D]), with a grain setting-deficient phenotype caused by overexpression of GSD1, a remorin gene with unknown function. GSD1 is expressed specifically in phloem companion cells and is localized in the PD and PM. We provide evidence to show that overexpression of GSD1 leads to deficient grain setting in rice, likely as a consequence of reduced sugar transport resulting from decreased PD permeability in phloem companion cells.     

Turnip mosaic virus Moves Systemically through Both Phloem and Xylem as Membrane-Associated Complexes

Plant viruses move systemically in plants through the phloem. They move as virions or as ribonucleic protein complexes, although it is not clear what these complexes are made of. The approximately 10-kb RNA genome of Turnip mosaic virus (TuMV) encodes a membrane protein, known as 6K₂, that induces endomembrane rearrangements for the formation of viral replication factories. These factories take the form of vesicles that contain viral RNA (vRNA) and viral replication proteins. In this study, we report the presence of 6K₂-tagged vesicles containing vRNA and the vRNA-dependent RNA polymerase in phloem sieve elements and in xylem vessels. Transmission electron microscopy observations showed the presence in the xylem vessels of vRNA-containing vesicles that were associated with viral particles. Stem-girdling experiments, which leave xylem vessels intact but destroy the surrounding tissues, confirmed that TuMV could establish a systemic infection of the plant by going through xylem vessels. Phloem sieve elements and xylem vessels from Potato virus X-infected plants also contained lipid-associated nonencapsidated vRNA, indicating that the presence of membrane-associated ribonucleic protein complexes in the phloem and xylem may not be limited to TuMV. Collectively, these studies indicate that viral replication factories could end up in the phloem and the xylem.Plant viruses use the host preexisting transport routes to propagate infection to the whole plant. After replication in the initially infected cells, viruses move cell to cell through plasmodesmata (PD) and start a new round of replication in the newly infected cells. This cycle is repeated until viruses reach vascular tissues, where they enter into the conducting tubes for systemic movement. Several studies have indicated that plant viruses are passively transported along the source-to-sink flow of photoassimilates and thus are believed to move systemically through the phloem (for review, see Hipper et al., 2013).The conducting tube of the phloem is the sieve element. The mature sieve element is enucleated and relies on the associated companion cells for the maintenance of its physiological function (Fisher et al., 1992). The specialized PD connecting one sieve element with one companion cell is called the pore plasmodesmal unit (PPU). Different from the other PDs, PPUs are always branched on the companion cell side but have only one channel on the sieve element side (Oparka and Turgeon, 1999). It is believed that the loading and uploading of viral material during phloem transport are through PPUs. Even though the size exclusion limit of PPUs (Kempers and Bel, 1997) is larger than that of the other PDs (Wolf et al., 1989; Derrick et al., 1990), PPUs should not allow, in their native state, virions or viral ribonucleoprotein (vRNP) complexes to pass through. It is thus believed that specific interactions between virus and host factors are required to allow the viral entity to go through. For instance, the movement protein of Cucumber mosaic virus (CMV) is targeted to PPUs (Blackman et al., 1998), suggesting that this viral protein modifies the size exclusion limit of PPUs and helps viral entry into sieve elements.Most plant viruses are assumed to move systemically through the phloem as virions. This assumption is based on the observation that Coat Protein (CP) deletions debilitating virus assembly prevent systemic infection (Brault et al., 2003; Zhang et al., 2013; Hipper et al., 2014). Some investigations showed the actual presence of virions in sieve elements. This is the case for the icosahedral Tobacco ringspot virus (Halk and McGuire, 1973), Carrot red leaf virus (Murant and Roberts, 1979), Potato leaf roll virus (Shepardson et al., 1980), and Beet western yellows virus (Hoefert, 1984). In addition, virions also were observed in phloem sap, such as the icosahedral CMV (Requena et al., 2006) and the rigid rod-shaped Cucumber green mottle mosaic virus (Simón-Buela and García-Arenal, 1999). Some viruses also are believed to move as ribonucleic protein (RNP) complexes, since systemic movement was observed in CP mutants where virion assembly was hindered. For instance, Tobacco rattle virus, Potato mop-top virus, Brome mosaic virus, and Tomato bushy stunt virus can still move systemically when the CP gene has been deleted from the viral genome (Swanson et al., 2002; Savenkov et al., 2003; Gopinath and Kao, 2007; Manabayeva et al., 2013). For potyviruses, it is still not clear if long-distance transport involves exclusively viral particles or if vRNP complexes also are implicated (Dolja et al., 1994, 1995; Cronin et al., 1995; Schaad et al., 1997; Kasschau and Carrington, 2001; Rajamaki and Valkonen, 2002). But whether virions or vRNP complexes are involved in viral movement, the full nature of the viral entity being implicated has not been defined.Xylem also is used for systemic infection of viruses, but its importance in viral transport generally has been overlooked. Vessel elements are the building blocks of xylem vessels, which constitute the major part of the water-upward-transporting system in a plant. The side walls of mature vessel elements contain pits, which are areas lacking a secondary cell wall; the end walls of the mature vessel elements are removed, and the openings are called perforation plates (Roberts and McCann, 2000). CP or virions of some plant viruses of all different shapes have been detected in the xylem vessels and/or guttation fluid, suggesting that these viruses may move systemically through xylem vessels. For example, the CP of the icosahedral Tomato bushy stunt virus (Manabayeva et al., 2013) and Rice yellow mottle virus (Opalka et al., 1998), the CP of the rigid rod-shaped Soilborne wheat mosaic virus (Verchot et al., 2001) and Cucumber green mottle mosaic virus (Moreno et al., 2004), and the flexuous rod-shaped Potato virus X (PVX; Betti et al., 2012) were detected in xylem vessels. Colocalization of anti-Rice yellow mottle virus antibodies and a cell wall marker for cellulosic β-(1-4)-d-glucans over vessel pit membranes suggests that the pit membranes might be a pathway for virus migration between vessels (Opalka et al., 1998). Moreover, flexuous rod-shaped virions of Zucchini yellow mosaic virus were found in both xylem vessels of root tissue and the guttation fluid (French and Elder, 1999). Finally, icosahedral Brome mosaic virus (Ding et al., 2001) and rigid rod-shaped Tomato mosaic virus and Pepper mild mottle virus (French et al., 1993) virions were found in guttation fluid. Guttation fluid originates from xylem exudate, indicating that these plant viruses can move through xylem within the infected plant. The above studies, however, mainly relied on electron microscopy and infection assays and may have missed the presence of other viral components that might be involved in transport.Turnip mosaic virus (TuMV) is a positive-strand RNA virus belonging to the family Potyviridae, genus Potyvirus, which contains around 30% of the currently known plant viruses and causes serious diseases in numerous crops (Shukla et al., 1994). Potyviruses are nonenveloped, flexuous rod-shaped particles of 680 to 900 nm in length and 11 to 13 nm in diameter. The genomic approximately 10-kb RNA encodes a polyprotein, which is processed into at least 11 mature proteins. TuMV remodels cellular membranes into viral factories, which are intracellular compartments involved in viral replication and movement. These compartments take the form of vesicles of approximately 100 nm in diameter originating from the endoplasmic reticulum (Grangeon et al., 2012). These vesicles contain viral RNA (vRNA) and viral and host proteins involved in vRNA replication (Beauchemin et al., 2007; Beauchemin and Laliberté, 2007; Dufresne et al., 2008; Huang et al., 2010; Grangeon et al., 2012). The viral membrane 6K₂ protein is involved in the membrane alterations and vesicle production (Beauchemin et al., 2007). The membrane-bound replication complexes can move intracellularly and cell to cell (Grangeon et al., 2013) at a rate of one cell being infected every 3 h (Agbeci et al., 2013). Intercellular trafficking of the replication complex is likely mediated by the PD-localized potyviral proteins Cytoplasmic Inclusion (CI) and P3N-PIPO (for N-terminal Half of P3 fused to the Pretty Interesting Potyviridae ORF; Carrington et al., 1998; Wei et al., 2010; Vijayapalani et al., 2012) as well as CP (Dolja et al., 1994, 1995), Viral Protein genome-linked (VPg; Nicolas et al., 1997; Rajamaki and Valkonen, 1999, 2002), and Helper Component-Proteinase (HC-Pro; Cronin et al., 1995; Kasschau et al., 1997; Rojas et al., 1997; Kasschau and Carrington, 2001), which are involved in both cell-to-cell and vascular movement.It is expected that, ultimately, TuMV reaches the vascular tissues of the plant, but how and under what form it is released into the conducting tubes are not known. To further understand viral spread and systemic movement, we investigated the distribution of 6K₂-tagged TuMV factories in all of the leaf and stem tissues other than the epidermal cells. We found TuMV factories in all tissues. Interestingly, we observed 6K₂-tagged vesicles, containing vRNA and viral replication proteins, in both phloem sieve elements and xylem vessels. We confirmed that TuMV could move systemically through xylem by a so-called stem-girdling assay, which induces cell death of the phloem without affecting xylem integrity. Hence, our study indicates that membrane-associated TuMV replication complexes are involved in the systemic movement of the virus.     

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.     

The Role of a Potassium Transporter OsHAK5 in Potassium Acquisition and Transport from Roots to Shoots in Rice at Low Potassium Supply Levels

In plants, K transporter (KT)/high affinity K transporter (HAK)/K uptake permease (KUP) is the largest potassium (K) transporter family; however, few of the members have had their physiological functions characterized in planta. Here, we studied OsHAK5 of the KT/HAK/KUP family in rice (Oryza sativa). We determined its cellular and tissue localization and analyzed its functions in rice using both OsHAK5 knockout mutants and overexpression lines in three genetic backgrounds. A β-glucuronidase reporter driven by the OsHAK5 native promoter indicated OsHAK5 expression in various tissue organs from root to seed, abundantly in root epidermis and stele, the vascular tissues, and mesophyll cells. Net K influx rate in roots and K transport from roots to aerial parts were severely impaired by OsHAK5 knockout but increased by OsHAK5 overexpression in 0.1 and 0.3 mm K external solution. The contribution of OsHAK5 to K mobilization within the rice plant was confirmed further by the change of K concentration in the xylem sap and K distribution in the transgenic lines when K was removed completely from the external solution. Overexpression of OsHAK5 increased the K-sodium concentration ratio in the shoots and salt stress tolerance (shoot growth), while knockout of OsHAK5 decreased the K-sodium concentration ratio in the shoots, resulting in sensitivity to salt stress. Taken together, these results demonstrate that OsHAK5 plays a major role in K acquisition by roots faced with low external K and in K upward transport from roots to shoots in K-deficient rice plants.Potassium (K) is one of the three most important macronutrients and the most abundant cation in plants. As a major osmoticum in the vacuole, K drives the generation of turgor pressure, enabling cell expansion. In the vascular tissue, K is an important participant in the generation of root pressure (for review, see Wegner, 2014 [including his new hypothesis]). In the phloem, K is critical for the transport of photoassimilates from source to sink (Marschner, 1996; Deeken et al., 2002; Gajdanowicz et al., 2011). In addition, enhancing K absorption and decreasing sodium (Na) accumulation is a major strategy of glycophytes in salt stress tolerance (Maathuis and Amtmann, 1999; Munns and Tester, 2008; Shabala and Cuin, 2008).Plants acquire K through K-permeable proteins at the root surface. Since available K concentration in the soil may vary by 100-fold, plants have developed multiple K uptake systems for adapting to this variability (Epstein et al., 1963; Grabov, 2007; Maathuis, 2009). In a classic K uptake experiment in barley (Hordeum vulgare), root K absorption has been described as a high-affinity and low-affinity biphasic transport process (Epstein et al., 1963). It is generally assumed that the low-affinity transport system (LATS) in the roots mediates K uptake in the millimolar range and that the activity of this system is insensitive to external K concentration (Maathuis and Sanders, 1997; Chérel et al., 2014). In contrast, the high-affinity transport system (HATS) was rapidly up-regulated when the supply of exogenous K was halted (Glass, 1976; Glass and Dunlop, 1978).The membrane transporters for K flux identified in plants are generally classified into three channels and three transporter families based on phylogenetic analysis (Mäser et al., 2001; Véry and Sentenac, 2003; Lebaudy et al., 2007; Alemán et al., 2011). For K uptake, it was predicted that, under most circumstances, K transporters function as HATS, while K-permeable channels mediate LATS (Maathuis and Sanders, 1997). However, a root-expressed K channel in Arabidopsis (Arabidopsis thaliana), Arabidopsis K Transporter1 (AKT1), mediates K absorption over a wide range of external K concentrations (Sentenac et al., 1992; Lagarde et al., 1996; Hirsch et al., 1998; Spalding et al., 1999), while evidence is accumulating that many K transporters, including members of the K transporter (KT)/high affinity K transporter (HAK)/K uptake permease (KUP) family, are low-affinity K transporters (Quintero and Blatt, 1997; Senn et al., 2001), implying that functions of plant K channels and transporters overlap at different K concentration ranges.Out of the three families of K transporters, cation proton antiporter (CPA), high affinity K/Na transporter (HKT), and KT/HAK/KUP, CPA was characterized as a K⁺(Na⁺)/H⁺ antiporter, HKT may cotransport Na and K or transport Na only (Rubio et al., 1995; Uozumi et al., 2000), while KT/HAK/KUP were predicted to be H⁺-coupled K⁺ symporters (Mäser et al., 2001; Lebaudy et al., 2007). KT/HAK/KUP were named by different researchers who first identified and cloned them (Quintero and Blatt, 1997; Santa-María et al., 1997). In plants, the KT/HAK/KUP family is the largest K transporter family, including 13 members in Arabidopsis and 27 members in the rice (Oryza sativa) genome (Rubio et al., 2000; Mäser et al., 2001; Bañuelos et al., 2002; Gupta et al., 2008). Sequence alignments show that genes of this family share relatively low homology to each other. The KT/HAK/KUP family was divided into four major clusters (Rubio et al., 2000; Gupta et al., 2008), and in cluster I and II, they were further separated into A and B groups. Genes of cluster I or II likely exist in all plants, cluster III is composed of genes from both Arabidopsis and rice, while cluster IV includes only four rice genes (Grabov, 2007; Gupta et al., 2008).The functions of KT/HAK/KUP were studied mostly in heterologous expression systems. Transporters of cluster I, such as AtHAK5, HvHAK1, OsHAK1, and OsHAK5, are localized in the plasma membrane (Kim et al., 1998; Bañuelos et al., 2002; Gierth et al., 2005) and exhibit high-affinity K uptake in the yeast Saccharomyces cerevisiae (Santa-María et al., 1997; Fu and Luan, 1998; Rubio et al., 2000) and in Escherichia coli (Horie et al., 2011). Transporters of cluster II, like AtKUP4 (TINY ROOT HAIRS1, TRH1), HvHAK2, OsHAK2, OsHAK7, and OsHAK10, could not complement the K uptake-deficient yeast (Saccharomyces cerevisiae) but were able to mediate K fluxes in a bacterial mutant; they might be tonoplast transporters (Senn et al., 2001; Bañuelos et al., 2002; Rodríguez-Navarro and Rubio, 2006). The function of transporters in clusters III and IV is even less known (Grabov, 2007).Existing data suggest that some KT/HAK/KUP transporters also may respond to salinity stress (Maathuis, 2009). The cluster I transporters of HvHAK1 mediate Na influx (Santa-María et al., 1997), while AtHAK5 expression is inhibited by Na (Rubio et al., 2000; Nieves-Cordones et al., 2010). Expression of OsHAK5 in tobacco (Nicotiana tabacum) BY2 cells enhanced the salt tolerance of these cells by accumulating more K without affecting their Na content (Horie et al., 2011).There are only scarce reports on the physiological function of KT/HAK/KUP in planta. In Arabidopsis, mutation of AtKUP2 (SHORT HYPOCOTYL3) resulted in a short hypocotyl, small leaves, and a short flowering stem (Elumalai et al., 2002), while a loss-of-function mutation of AtKUP4 (TRH1) resulted in short root hairs and a loss of gravity response in the root (Rigas et al., 2001; Desbrosses et al., 2003; Ahn et al., 2004). AtHAK5 is the only system currently known to mediate K uptake at concentrations below 0.01 mm (Rubio et al., 2010) and provides a cesium uptake pathway (Qi et al., 2008). AtHAK5 and AtAKT1 are the two major physiologically relevant molecular entities mediating K uptake into roots in the range between 0.01 and 0.05 mm (Pyo et al., 2010; Rubio et al., 2010). AtAKT1 may contribute to K uptake within the K concentrations that belong to the high-affinity system described by Epstein et al. (1963).Among all 27 members of the KT/HAK/KUP family in rice, OsHAK1, OsHAK5, OsHAK19, and OsHAK20 were grouped in cluster IB (Gupta et al., 2008). These four rice HAK members share 50.9% to 53.4% amino acid identity with AtHAK5. OsHAK1 was expressed in the whole plant, with maximum expression in roots, and was up-regulated by K deficiency; it mediated high-affinity K uptake in yeast (Bañuelos et al., 2002). In this study, we examined the tissue-specific localization and the physiological functions of OsHAK5 in response to variation in K supply and to salt stress in rice. By comparing K uptake and translocation in OsHAK5 knockout (KO) mutants and in OsHAK5-overexpressing lines with those in their respective wild-type lines supplied with different K concentrations, we found that OsHAK5 not only mediates high-affinity K acquisition but also participates in root-to-shoot K transport as well as in K-regulated salt tolerance.