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.     

Self-Incompatibility-Induced Programmed Cell Death in Field Poppy Pollen Involves Dramatic Acidification of the Incompatible Pollen Tube Cytosol

Self-incompatibility (SI) is an important genetically controlled mechanism to prevent inbreeding in higher plants. SI involves highly specific interactions during pollination, resulting in the rejection of incompatible (self) pollen. Programmed cell death (PCD) is an important mechanism for destroying cells in a precisely regulated manner. SI in field poppy (Papaver rhoeas) triggers PCD in incompatible pollen. During SI-induced PCD, we previously observed a major acidification of the pollen cytosol. Here, we present measurements of temporal alterations in cytosolic pH ([pH]_cyt); they were surprisingly rapid, reaching pH 6.4 within 10 min of SI induction and stabilizing by 60 min at pH 5.5. By manipulating the [pH]_cyt of the pollen tubes in vivo, we show that [pH]_cyt acidification is an integral and essential event for SI-induced PCD. Here, we provide evidence showing the physiological relevance of the cytosolic acidification and identify key targets of this major physiological alteration. A small drop in [pH]_cyt inhibits the activity of a soluble inorganic pyrophosphatase required for pollen tube growth. We also show that [pH]_cyt acidification is necessary and sufficient for triggering several key hallmark features of the SI PCD signaling pathway, notably activation of a DEVDase/caspase-3-like activity and formation of SI-induced punctate actin foci. Importantly, the actin binding proteins Cyclase-Associated Protein and Actin-Depolymerizing Factor are identified as key downstream targets. Thus, we have shown the biological relevance of an extreme but physiologically relevant alteration in [pH]_cyt and its effect on several components in the context of SI-induced events and PCD.Programmed cell death (PCD) in plants is relatively well documented and characterized (Jones and Dangl, 1996; van Doorn, 2011; van Doorn et al., 2011). There is considerable biochemical evidence for the involvement of caspase-like activities in plant PCD (van Doorn and Woltering, 2005). For example, the vacuolar processing enzyme has YVADase (caspase-1-like) activity (Hatsugai et al., 2004; Rojo et al., 2004; Hara-Nishimura et al., 2005), DEVDase (caspase-3-like) and YVADases are associated with PCD in several plant systems (del Pozo and Lam, 1998; Korthout et al., 2000; Danon et al., 2004), and VEIDase (caspase-6-like) is the main caspase-like activity involved in embryonic pattern formation (Bozhkov et al., 2004). However, because plants have no caspase gene homologs (Sanmartín et al., 2005), the nature of their caspase-like enzymes is the subject of considerable debate. Vacuolar cell death is one of two major classes of PCD in plants (van Doorn et al., 2011). It is thought that collapse of the vacuole is a key irreversible step in several plant PCD systems, including during tissue and organ formation, such as the classic differentiation of tracheary elements (Hara-Nishimura and Hatsugai, 2011). Exactly how this is achieved and what processes are involved remain unknown. Until very recently, it was generally thought that the rupturing vacuole releases proteases, hydrolases, and nucleases, allowing cellular disassembly by an autophagy-like process. Some PCD systems cannot be assigned to either class; these include PCD triggered by the hypersensitive response to biotrophic pathogens, PCD in cereal endosperm, and self-incompatibility (SI)-induced PCD (van Doorn et al., 2011).SI is a genetically controlled pollen-pistil cell-cell recognition system. Self-pollen is recognized by the stigma as being genetically identical, resulting in inhibition of pollen tube growth. Most SI systems use tightly linked polymorphic genes: the pollen (male) and pistil (female) S-determinants. In field poppy (Papaver rhoeas), the S-determinants are a 14-kD signaling ligand field poppy stigma S (PrsS) and a unique transmembrane protein field poppy pollen S (PrpS; Foote et al., 1994; Wheeler et al., 2010). These interact in an S-specific manner, and increases in cytosolic free calcium ([Ca2+]_cyt) are triggered in incompatible pollen tubes (Franklin-Tong et al., 1993), resulting in phosphorylation of soluble inorganic pyrophosphatases (sPPases; Rudd et al., 1996; de Graaf et al., 2006), activation of a Mitogen-Activated Protein Kinase (MAPK; Rudd et al., 2003), and increases in reactive oxygen species (ROS) and nitric oxide (Wilkins et al., 2011, 2014). Most of these components are integrated into a signaling network leading to PCD (Bosch et al., 2008; Wilkins et al., 2014). The actin cytoskeleton is a key target in the field poppy SI response, undergoing depolymerization (Snowman et al., 2002) followed by polymerization into highly stable F-actin foci decorated with the actin binding proteins (ABPs) Actin-Depolymerizing Factor (ADF) and Cyclase-Associated Protein (CAP; Poulter et al., 2010, 2011), with both processes being involved in mediating PCD (Thomas et al., 2006). A major player in SI-mediated PCD is a caspase-3-like/DEVDase-like activity (Thomas and Franklin-Tong, 2004; Bosch and Franklin-Tong, 2007). The SI-induced caspase-3-like/DEVDase exhibits maximum substrate cleavage in vitro at pH 5, with peak activity 5 h after SI induction in vivo (Bosch and Franklin-Tong, 2007). The low pH optimum for this caspase-3-like/DEVDase activity is unusual, because most of the cytosolic plant caspase-like activities identified to date have optimal activity close to normal physiological pH (approximate pH, 6.5–7.0; Korthout et al., 2000; Bozhkov et al., 2004; Coffeen and Wolpert, 2004). Because the SI-induced cytosolic-located DEVDase requires a low pH for activity, this suggested that, during SI, the pollen tube cytosol undergoes dramatic acidification. In vivo pH measurements of the cytosol at 1 to 4 h after SI induction confirmed this, when cytosolic pH ([pH]_cyt) had dropped from pH 6.9 to pH 5.5 (Bosch and Franklin-Tong, 2007). This fits the in vitro pH optimum of the caspase-3-like/DEVDase almost exactly, implicating pollen cytosolic acidification as playing a vital role in creating optimal conditions for the activation of the caspase-3-like/DEVDase-like activity and progression of PCD.Under normal cellular conditions, [pH]_cyt is between approximately 6.9 and 7.5 (Kurkdjian and Guern, 1989; Felle, 2001). Pollen tubes, like other tip-growing cells, have [pH]_cyt gradients (Gibbon and Kropf, 1994; Feijó et al., 1999). The [pH]_cyt of the pollen tube shank is an approximate pH of 6.9 to 7.11 (Fricker et al., 1997; Messerli and Robinson, 1998). There has been much debate about the [pH]_cyt gradient, comprising an apical domain with an approximate pH of 6.8 and a subapical alkaline band with an approximate pH of 7.2 to 7.8 in Lilium longiflorum and Lilium formosanum pollen tubes (Fricker et al., 1997; Messerli and Robinson, 1998; Feijó et al., 2001; Lovy-Wheeler et al., 2006). Oscillations of [pH]_cyt between approximate pH values of 6.9 and 7.3 have been linked to tip growth in L. formosanum pollen tubes (Lovy-Wheeler et al., 2006). The vacuole and the apoplast have a highly acidic pH between pH 5 and pH 6 (Katsuhara et al., 1989; Feijó et al., 1999). The majority of studies of pH changes in plant cells reports modest, transient changes in [pH]_cyt of approximately 0.4 and 0.7 pH units during development, gravitropic responses, decreases in light intensity, and addition of elicitors, hormones, and other treatments. For example, during root hair development in Arabidopsis (Arabidopsis thaliana), root [pH]_cyt was elevated from an approximate pH of 7.3 to 7.7 (Bibikova et al., 1998). Root gravitropic responses stimulate small transient [pH]_cyt alterations (Scott and Allen, 1999; Fasano et al., 2001; Johannes et al., 2001). More recently, it has been shown that the [pH]_cyt drops during PCD controlling root cap development; however, exactly how many units the [pH]_cyt decreased was not measured (Fendrych et al., 2014). Other studies investigating [pH]_cyt in response to physiologically relevant signals also report small transient alterations. Light-adapted cells respond to a decrease in light intensity with a rapid transient cytosolic acidification by approximately 0.3 pH units (Felle et al., 1986). Addition of nodulation factors resulted in an increase of 0.2 pH units in root hairs (Felle et al., 1998), and abscisic acid increased the [pH]_cyt of guard cells by 0.3 pH units (Blatt and Armstrong, 1993). Changes in [pH]_cyt are thought to activate stress responses (Felle, 2001). Elicitor treatments resulted in a [pH]_cyt drop of between 0.4 and 0.7 pH units in suspension cells (Mathieu et al., 1996; Kuchitsu et al., 1997), a drop of 0.2 pH units in Nitellopsis obtusa cells treated with salt (Katsuhara et al., 1989), and a drop of 0.3 to 0.7 pH units in Eschscholzia californica (Roos et al., 1998).Here, we investigate SI-induced acidification of the cytosol, providing measurements of physiologically relevant temporal alterations in [pH]_cyt, and identify key targets of this, providing mechanistic insights into these events. The SI-induced acidification plays a pivotal role in the activation of a caspase-3-like/DEVDase activity, the formation of punctate F-actin foci, and ABP localization during SI PCD. We investigate the vacuole as a potential contributor to SI-induced [pH]_cyt acidification.     

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.     

New Arabidopsis Advanced Intercross Recombinant Inbred Lines Reveal Female Control of Nonrandom Mating

Female control of nonrandom mating has never been genetically established, despite being linked to inbreeding depression and sexual selection. In order to map the loci that control female-mediated nonrandom mating, we constructed a new advanced intercross recombinant inbred line (RIL) population derived from a cross between Arabidopsis (Arabidopsis thaliana) accessions Vancouver (Van-0) and Columbia (Col-0) and mapped quantitative trait loci (QTLs) responsible for nonrandom mating and seed yield traits. We genotyped a population of 490 RILs. A subset of these lines was used to construct an expanded map of 1,061.4 centimorgans with an average interval of 6.7 ± 5.3 centimorgans between markers. QTLs were then mapped for female- and male-mediated nonrandom mating and seed yield traits. To map the genetic loci responsible for female-mediated nonrandom mating and seed yield, we performed mixed pollinations with genetically marked Col-0 pollen and Van-0 pollen on RIL pistils. To map the loci responsible for male-mediated nonrandom mating and seed yield, we performed mixed pollinations with genetically marked Col-0 and RIL pollen on Van-0 pistils. Composite interval mapping of these data identified four QTLs that control female-mediated nonrandom mating and five QTLs that control female-mediated seed yield. We also identified four QTLs that control male-mediated nonrandom mating and three QTLs that control male-mediated seed yield. Epistasis analysis indicates that several of these loci interact. To our knowledge, the results of these experiments represent the first time female-mediated nonrandom mating has been genetically defined.The process of pollination offers plants the opportunity to selectively breed. For example, in pollinations that include more than one pollen population, pollen often show differential siring ability. This process is called nonrandom mating. Although pollen may fail in pollinations because they are self pollen in an obligate outcrossing plant or pollen from a different species, we focus our studies on differential siring ability of compatible, conspecific mates (Hogenboom, 1973, 1975; Williams et al., 1999; de Nettancourt, 2001; Husband et al., 2002; Wheeler et al., 2009; Meng et al., 2011; Nasrallah, 2011). Nonrandom mating at this level has received intense interest for its potential to avoid inbreeding depression and its potential to be the result of sexual selection (Charnov, 1979; Mulcahy, 1979; Willson, 1979; Queller, 1983; Stephenson and Bertin, 1983; Willson and Burley, 1983; Marshall and Ellstrand, 1986; Charlesworth and Charlesworth, 1987; Mulcahy and Mulcahy, 1987; Cruzan, 1990; Quesada et al., 1993; Snow, 1994; Paschke et al., 2002; Skogsmyr and Lankinen, 2002; Stephenson et al., 2003; Armbruster and Rogers, 2004; Bernasconi et al., 2004; Lankinen and Armbruster, 2007). Despite a long history of theoretical and experimental attention, very little is known about the underlying genetics that govern the process (Carlson et al., 2011).One challenge in understanding the genetics of nonrandom mating lies in its complexity, potentially involving multiple distinct pathways specific to either female or male tissues. Physiologically, postpollination nonrandom mating may be a result of intrinsic differences in pollen competitive abilities (male-mediated nonrandom mating). A number of experimental strategies have been employed to demonstrate male-mediated control of nonrandom mating. For example, experiments in radish (Raphanus sativus) found that some pollen sire more seeds than others in mixed pollinations across a range of maternal plants, demonstrating consistency of male function (Marshall and Ellstrand, 1986, 1988; Mitchell and Marshall, 1998). More direct measures of male function, such as in vitro and in vivo pollen tube growth rates, verify variation in male function and demonstrable impact on nonrandom mating (Snow and Spira, 1991a, 1991b; Pasonen et al., 1999; Skogsmyr and Lankinen, 1999; Stephenson et al., 2001; Lankinen and Skogsmyr, 2002; Lankinen et al., 2009). Finally, recent work in our laboratory has directly mapped the genetic loci responsible for the control of male-mediated nonrandom mating in Arabidopsis (Arabidopsis thaliana; Carlson et al., 2011).Alternatively, or concurrently, nonrandom mating can be the result of differential interaction between the female tissue and competing pollen populations or seeds (female-mediated nonrandom mating). Establishing the female role in nonrandom mating has been more challenging, as most study designs involve the deposition of pollen from multiple donors and thus include the confounding variable of pollen competition. Despite this challenge, a number of experimental strategies have been devised to explore the role of the female in nonrandom mating. For example, a number of studies demonstrate that maternal identity influences nonrandom mating patterns (Marshall and Ellstrand, 1986, 1988; Snow and Mazer, 1988; Johnston, 1993; Marshall et al., 2000; Carlson et al., 2009, 2013). Studies have also established that manipulation of watering or nutrient regimes of maternal plants changes the patterns and magnitude of nonrandom mating (Marshall and Diggle, 2001; Shaner and Marshall, 2003; Haileselassie et al., 2005; Marshall et al., 2007). These studies and others implicate the identity and condition of the female in the process of nonrandom mating. Despite a long history of research, genetic control of female-mediated nonrandom mating has never been demonstrated, and the identity of the genes involved remains unexplored.In previous work, we developed a system in Arabidopsis to assay nonrandom mating and showed its utility for genetically mapping the loci responsible (Carlson et al., 2009, 2011). Pursuing the genetics of nonrandom mating in a largely selfing plant such as Arabidopsis provides both theoretical and practical advantages. First, outcrossing plants carry higher levels of heterozygosity that produce pollen populations that display different phenotypes because of segregating alleles. This complicates genetic analysis. Also, in outcrossing plants that carry genetic load, reproductive success is context dependent. Pollinations with self pollen or pollen from genetically similar plants often lead to poor reproductive outcomes. For example, in mixed pollinations in generally outcrossing self-compatible plants that include self pollen, self pollen often sire a disproportionally low number of seeds (Bateman, 1956; Weller and Ornduff, 1977; Bowman, 1987; Eckert and Barrett, 1994; Jones, 1994; Hauser and Siegismund, 2000; Teixeira et al., 2009), but other findings have been reported (Sork and Schemske, 1992; Johnston, 1993). Thus, in outcrossing plants, gene variants that influence reproductive success, parental relatedness, and segregating heterozygosity all influence reproductive outcomes. Two of these factors are essentially eliminated by studying plant populations that have historically selfed. As outcrossing populations become increasingly self-fertilizing, they both lose heterozygosity, and their genetic load is purged (Lande and Schemske, 1985; Schemske and Lande, 1985; Charlesworth and Charlesworth, 1987; Lande et al., 1994; Byers and Waller, 1999; Crnokrak and Barrett, 2002). This is the case for Arabidopsis, whose tested populations show relatively low levels of heterozygosity and little evidence for the early-acting inbreeding depression that is indicative of genetic load (Bakker et al., 2006; Bomblies et al., 2010; Platt et al., 2010; Carlson et al., 2013). Thus, this system provides an excellent opportunity to identify and explore the genetic variation in differential reproduction that develops or persists in plant populations unrelated to inbreeding depression.Using this system, we previously identified potential female control of nonrandom mating in mixed pollinations between Vancouver (Van-0) and Columbia (Col-0) accessions of Arabidopsis (Carlson et al., 2009). When Van-0 and genetically marked Col-0 (Col-NPTII) pollen compete on Col-0 pistils, Col-NPTII pollen sire 43% of the progeny, while Van-0 pollen sire 57%. When these pollen compete on Van-0 pistils, Col-NPTII pollen sire 67.5% of the progeny, while Van-0 pollen sire 32.5%. This system offers us, to our knowledge for the first time, the opportunity to genetically define female-mediated nonrandom mating and map the loci responsible.In order to genetically map female control of nonrandom mating, we constructed a new advanced intercross recombinant inbred line (RIL) mapping population derived from a cross between Van-0 and Col-0 accessions of Arabidopsis. RILs are powerful tools that allow high-resolution genetic mapping of loci that direct complex traits. Each RIL contains chromosomes that are defined homozygous patchworks of parental DNA, in this case Van-0 and Col-0. By phenotyping these lines, we can statistically associate nonrandom mating and seed yield phenotypes with chromosomal regions. We chose these two accessions because (1) our previous experiments predict clear female control of nonrandom mating and (2) we have previously mapped male-mediated nonrandom mating controls using a Col-4/Landsberg mapping population (a population that does not display female control of nonrandom mating; Carlson et al., 2011). Thus, this new population provides us the opportunity to map loci that control female nonrandom mating and investigate the degree of conservation of loci that affect male-mediated nonrandom mating. We use this new mapping population to perform quantitative trait locus (QTL) mapping and identify multiple loci that direct both female- and male-mediated control of nonrandom mating and seed yield traits.     

ABNORMAL POLLEN TUBE GUIDANCE1, an Endoplasmic Reticulum-Localized Mannosyltransferase Homolog of GLYCOSYLPHOSPHATIDYLINOSITOL10 in Yeast and PHOSPHATIDYLINOSITOL GLYCAN ANCHOR BIOSYNTHESIS B in Human,Is Required for Arabidopsis Pollen Tube Micropylar Guidance and Embryo Development

The perception and response of pollen tubes to the female guidance signals are crucial for directional pollen tube growth inside female tissues, which leads to successful reproduction. In pursuing the mechanisms underlying this biological process, we identified the Arabidopsis (Arabidopsis thaliana) abnormal pollen tube guidance1 (aptg1) mutant, whose pollen tubes showed compromised micropylar guidance. In addition to its male defect, the aptg1 mutant showed embryo lethality. APTG1 encodes a putative mannosyltransferase homolog to human PHOSPHATIDYLINOSITOL GLYCAN ANCHOR BIOSYNTHESIS B and yeast (Saccharomyces cerevisiae) GLYCOSYLPHOSPHATIDYLINOSITOL10 (GPI10), both of which are involved in the biosynthesis of GPI anchors. We found that APTG1 was expressed in most plant tissues, including mature pollen, pollen tubes, mature embryo sacs, and developing embryos. By fluorescence colabeling, we showed that APTG1 was localized in the endoplasmic reticulum, where GPI anchors are synthesized. Disruption of APTG1 affected the localization of COBRA-LIKE10, a GPI-anchored protein important for pollen tube growth and guidance. The results shown here demonstrate that APTG1 is involved in both vegetative and reproductive development in Arabidopsis, likely through processing and proper targeting of GPI-anchored proteins.Double fertilization is the biological basis for seed propagation and plant reproduction in angiosperms. Pollen tubes grow through maternal tissue to deliver the immobile sperm cells into the female gametophyte (embryo sac). During this process, pollen tube guidance into the micropyle is a critical step and is precisely regulated (Dresselhaus and Franklin-Tong, 2013). Female guidance signals are generated by both sporophytic and gametophytic tissues and operate at different stages during pollen tube growth. The sporophytic signal directs the growth of pollen tubes in the stigma, style, and transmitting tract. The signal that induces pollen tubes to turn to the funiculus and grow into the micropyle is termed gametophytic guidance (Shimizu and Okada, 2000; Higashiyama et al., 2003). Extensive cellular and genetic studies have demonstrated that female gametophytes play key roles in the micropylar guidance of pollen tubes (Kasahara et al., 2005; Márton et al., 2005; Chen et al., 2007; Alandete-Saez et al., 2008; Okuda et al., 2009; Kessler and Grossniklaus, 2011; Takeuchi and Higashiyama, 2011). The molecular natures of such guidance signals have been gradually revealed in recent years (i.e. small peptides secreted by the female gametophyte, egg apparatus, or synergid cells; Márton et al., 2005; Jones-Rhoades et al., 2007; Okuda et al., 2009).Pollen tubes need to perceive the female guidance signals at the cell surface to initiate intracellular responses for directional growth. However, the mechanisms of pollen tube perception are still obscure. A few male factors involved in signal perception during pollen tube growth into ovules have been identified. For example, the Arabidopsis (Arabidopsis thaliana) sperm cell-specific protein HAPLESS2/GENERATIVE CELL-SPECIFIC1 was necessary for pollen tubes to target the micropyle (von Besser et al., 2006). Arabidopsis CATION/PROTON EXCHANGER21 (CHX21) and CHX23 encode K⁺ transporters in growing pollen tubes. Pollen grains of the chx21 chx23 double mutant germinated and extended a normal tube in the transmitting tract, but their targeting of the funiculus failed (Lu et al., 2011). Arabidopsis POLLEN DEFECTIVE IN GUIDANCE1 (POD1) was expressed in pollen grains, pollen tubes, and synergid cells. The pod1 pollen tubes showed defective micropylar guidance (Li et al., 2011). The tip of the pollen tube has been hypothesized to be the site of cue perception for micropyle-directed growth. The Arabidopsis Rab GTPase RABA4D was localized at the tips of growing pollen tubes. Pollen tubes with defective RABA4D had severely reduced growth rates and ovule targeting (Szumlanski and Nielsen, 2009). Recently, two receptor-like kinases at the apical plasma membrane (PM) of growing pollen tubes, LOST IN POLLEN TUBE GUIDANCE1 (LIP1) and LIP2, were demonstrated to guide pollen tubes to the micropyle by perceiving the AtLURE1 signal from synergid cells (Liu et al., 2013).Glycosylphosphatidylinositol (GPI) anchoring provides a strategy for targeting proteins to the outer layer of the PMs in eukaryotic cells. GPI anchors are synthesized inside the endoplasmic reticulum (ER) and are attached to proteins by posttranslational modifications in the ER. After processing, GPI-anchored proteins (GPI-APs) are transported to the cell surface following an unknown trafficking route and anchored at the cell surface (Maeda and Kinoshita, 2011). GPI-APs play very important roles in plant reproductive development (Gillmor et al., 2005; Ching et al., 2006; DeBono et al., 2009). An Arabidopsis putative GPI-AP, LORELEI, functioned in pollen tube reception of female signals, double fertilization, and early seed development (Capron et al., 2008; Tsukamoto et al., 2010). Arabidopsis COBRA-LIKE10 (COBL10), a GPI-AP, regulates the polar deposition of wall components in pollen tubes growing inside female tissues and is critical for micropylar guidance (Li et al., 2013). The conserved backbone of GPI anchors in eukaryotes is ethanolamine phosphate-6-Man-α-1,2-Man-α-1,6-Man-α-1,4-glucosamine-α-1,6-myoinositol phospholipid. During the biosynthesis of GPI anchors, monosaccharides, fatty acids, and phosphoethanolamines are sequentially added onto phosphatidylinositol. This process involves at least 16 enzymes and cofactors in mammals, including PHOSPHATIDYLINOSITOL GLYCAN ANCHOR BIOSYNTHESIS (PIG) A, B, C, F, G, H, L, M, N, O, P, Q, V, W, X, and Y (Maeda and Kinoshita, 2011). The core structure of the GPI anchor contains three Man residues donated by the substrate dolichol-phosphate-Man. GPI mannosyltransferases were required for adding the three Man residues of the GPI anchor in the ER lumen (Maeda and Kinoshita, 2011). Arabidopsis PEANUT1 (PNT1) is a homolog of the mammalian GPI mannosyltransferase PIG-M, involved in the addition of the first Man during the biosynthesis of the GPI anchor. The pnt1 mutant showed the defect of pollen viability and embryo development (Gillmor et al., 2005). PIG-B of human and GPI10 of yeast (Saccharomyces cerevisiae) encode GLYCOSYLPHOSPHATIDYLINOSITOL MANNOSYLTRANSFERASE3, involved in the addition of the third Man during the biosynthesis of the GPI anchor (Takahashi et al., 1996; Sütterlin et al., 1998). Mutation of PIG-B and GPI10 resulted in the accumulation of the GPI intermediate Man2-glucosamine-(acyl) phosphatidylinositol and led to cell death in yeast.In this study, we identified the ER-localized ABNORMAL POLLEN TUBE GUIDANCE1 (APTG1), an Arabidopsis homolog of PIG-B and GPI10. Pollen tubes of the aptg1 mutant showed compromised directional growth to the micropyle and lost the apical PM localization of COBL10. Besides the male defect, the mutant showed embryo lethality. In addition, reducing the expression of APTG1 resulted in defective seedling growth, indicating that APTG1 plays important roles in both reproductive and vegetative development.     

Evolution of Conifer Diterpene Synthases: Diterpene Resin Acid Biosynthesis in Lodgepole Pine and Jack Pine Involves Monofunctional and Bifunctional Diterpene Synthases

Abscisic acid (ABA) induces stomatal closure and inhibits light-induced stomatal opening. The mechanisms in these two processes are not necessarily the same. It has been postulated that the ABA receptors involved in opening inhibition are different from those involved in closure induction. Here, we provide evidence that four recently identified ABA receptors (PYRABACTIN RESISTANCE1 [PYR1], PYRABACTIN RESISTANCE-LIKE1 [PYL1], PYL2, and PYL4) are not sufficient for opening inhibition in Arabidopsis (Arabidopsis thaliana). ABA-induced stomatal closure was impaired in the pyr1/pyl1/pyl2/pyl4 quadruple ABA receptor mutant. ABA inhibition of the opening of the mutant’s stomata remained intact. ABA did not induce either the production of reactive oxygen species and nitric oxide or the alkalization of the cytosol in the quadruple mutant, in accordance with the closure phenotype. Whole cell patch-clamp analysis of inward-rectifying K⁺ current in guard cells showed a partial inhibition by ABA, indicating that the ABA sensitivity of the mutant was not fully impaired. ABA substantially inhibited blue light-induced phosphorylation of H⁺-ATPase in guard cells in both the mutant and the wild type. On the other hand, in a knockout mutant of the SNF1-related protein kinase, srk2e, stomatal opening and closure, reactive oxygen species and nitric oxide production, cytosolic alkalization, inward-rectifying K⁺ current inactivation, and H⁺-ATPase phosphorylation were not sensitive to ABA.The phytohormone abscisic acid (ABA), which is synthesized in response to abiotic stresses, plays a key role in the drought hardiness of plants. Reducing transpirational water loss through stomatal pores is a major ABA response (Schroeder et al., 2001). ABA promotes the closure of open stomata and inhibits the opening of closed stomata. These effects are not simply the reverse of one another (Allen et al., 1999; Wang et al., 2001; Mishra et al., 2006).A class of receptors of ABA was identified (Ma et al., 2009; Park et al., 2009; Santiago et al., 2009; Nishimura et al., 2010). The sensitivity of stomata to ABA was strongly decreased in quadruple and sextuple mutants of the ABA receptor genes PYRABACTIN RESISTANCE/PYRABACTIN RESISTANCE-LIKE/REGULATORY COMPONENT OF ABSCISIC ACID RECEPTOR (PYR/PYL/RCAR; Nishimura et al., 2010; Gonzalez-Guzman et al., 2012). The PYR/PYL/RCAR receptors are involved in the early ABA signaling events, in which a sequence of interactions of the receptors with PROTEIN PHOSPHATASE 2Cs (PP2Cs) and subfamily 2 SNF1-RELATED PROTEIN KINASES (SnRK2s) leads to the activation of downstream ABA signaling targets in guard cells (Cutler et al., 2010; Kim et al., 2010; Weiner et al., 2010). Studies of Commelina communis and Vicia faba suggested that the ABA receptors involved in stomatal opening are not the same as the ABA receptors involved in stomatal closure (Allan et al., 1994; Anderson et al., 1994; Assmann, 1994; Schwartz et al., 1994). The roles of PYR/PYL/RCAR in either stomatal opening or closure remained to be elucidated.Blue light induces stomatal opening through the activation of plasma membrane H⁺-ATPase in guard cells that generates an inside-negative electrochemical gradient across the plasma membrane and drives K⁺ uptake through voltage-dependent inward-rectifying K⁺ channels (Assmann et al., 1985; Shimazaki et al., 1986; Blatt, 1987; Schroeder et al., 1987; Thiel et al., 1992). Phosphorylation of the penultimate Thr of the plasma membrane H⁺-ATPase is a prerequisite for blue light-induced activation of the H⁺-ATPase (Kinoshita and Shimazaki, 1999, 2002). ABA inhibits H⁺-ATPase activity through dephosphorylation of the penultimate Thr in the C terminus of the H⁺-ATPase in guard cells, resulting in prevention of the opening (Goh et al., 1996; Zhang et al., 2004; Hayashi et al., 2011). Inward-rectifying K⁺ currents (I_Kin) of guard cells are negatively regulated by ABA in addition to through the decline of the H⁺ pump-driven membrane potential difference (Schroeder and Hagiwara, 1989; Blatt, 1990; McAinsh et al., 1990; Schwartz et al., 1994; Grabov and Blatt, 1999; Saito et al., 2008). This down-regulation of ion transporters by ABA is essential for the inhibition of stomatal opening.A series of second messengers has been shown to mediate ABA-induced stomatal closure. Reactive oxygen species (ROS) produced by NADPH oxidases play a crucial role in ABA signaling in guard cells (Pei et al., 2000; Zhang et al., 2001; Kwak et al., 2003; Sirichandra et al., 2009; Jannat et al., 2011). Nitric oxide (NO) is an essential signaling component in ABA-induced stomatal closure (Desikan et al., 2002; Guo et al., 2003; Garcia-Mata and Lamattina, 2007; Neill et al., 2008). Alkalization of cytosolic pH in guard cells is postulated to mediate ABA-induced stomatal closure in Arabidopsis (Arabidopsis thaliana) and Pisum sativum and Paphiopedilum species (Irving et al., 1992; Gehring et al., 1997; Grabov and Blatt, 1997; Suhita et al., 2004; Gonugunta et al., 2008). These second messengers transduce environmental signals to ion channels and ion transporters that create the driving force for stomatal movements (Ward et al., 1995; MacRobbie, 1998; Garcia-Mata et al., 2003).In this study, we examined the mobilization of second messengers, the inactivation of I_Kin, and the suppression of H⁺-ATPase phosphorylation evoked by ABA in Arabidopsis mutants to clarify the downstream signaling events of ABA signaling in guard cells. The mutants included a quadruple mutant of PYR/PYL/RCARs, pyr1/pyl1/pyl2/pyl4, and a mutant of a SnRK2 kinase, srk2e.