Characterization of the Possible Roles for B Class MADS Box Genes in Regulation of Perianth Formation in Orchid

To investigate sepal/petal/lip formation in Oncidium Gower Ramsey, three paleoAPETALA3 genes, O. Gower Ramsey MADS box gene5 (OMADS5; clade 1), OMADS3 (clade 2), and OMADS9 (clade 3), and one PISTILLATA gene, OMADS8, were characterized. The OMADS8 and OMADS3 mRNAs were expressed in all four floral organs as well as in vegetative leaves. The OMADS9 mRNA was only strongly detected in petals and lips. The mRNA for OMADS5 was only strongly detected in sepals and petals and was significantly down-regulated in lip-like petals and lip-like sepals of peloric mutant flowers. This result revealed a possible negative role for OMADS5 in regulating lip formation. Yeast two-hybrid analysis indicated that OMADS5 formed homodimers and heterodimers with OMADS3 and OMADS9. OMADS8 only formed heterodimers with OMADS3, whereas OMADS3 and OMADS9 formed homodimers and heterodimers with each other. We proposed that sepal/petal/lip formation needs the presence of OMADS3/8 and/or OMADS9. The determination of the final organ identity for the sepal/petal/lip likely depended on the presence or absence of OMADS5. The presence of OMADS5 caused short sepal/petal formation. When OMADS5 was absent, cells could proliferate, resulting in the possible formation of large lips and the conversion of the sepal/petal into lips in peloric mutants. Further analysis indicated that only ectopic expression of OMADS8 but not OMADS5/9 caused the conversion of the sepal into an expanded petal-like structure in transgenic Arabidopsis (Arabidopsis thaliana) plants.The ABCDE model predicts the formation of any flower organ by the interaction of five classes of homeotic genes in plants (Yanofsky et al., 1990; Jack et al., 1992; Mandel et al., 1992; Goto and Meyerowitz, 1994; Jofuku et al., 1994; Pelaz et al., 2000, 2001; Theißen and Saedler, 2001; Pinyopich et al., 2003; Ditta et al., 2004; Jack, 2004). The A class genes control sepal formation. The A, B, and E class genes work together to regulate petal formation. The B, C, and E class genes control stamen formation. The C and E class genes work to regulate carpel formation, whereas the D class gene is involved in ovule development. MADS box genes seem to have a central role in flower development, because most ABCDE genes encode MADS box proteins (Coen and Meyerowitz, 1991; Weigel and Meyerowitz, 1994; Purugganan et al., 1995; Rounsley et al., 1995; Theißen and Saedler, 1995; Theißen et al., 2000; Theißen, 2001).The function of B group genes, such as APETALA3 (AP3) and PISTILLATA (PI), has been thought to have a major role in specifying petal and stamen development (Jack et al., 1992; Goto and Meyerowitz, 1994; Krizek and Meyerowitz, 1996; Kramer et al., 1998; Hernandez-Hernandez et al., 2007; Kanno et al., 2007; Whipple et al., 2007; Irish, 2009). In Arabidopsis (Arabidopsis thaliana), mutation in AP3 or PI caused identical phenotypes of second whorl petal conversion into a sepal structure and third flower whorl stamen into a carpel structure (Bowman et al., 1989; Jack et al., 1992; Goto and Meyerowitz, 1994). Similar homeotic conversions for petal and stamen were observed in the mutants of the AP3 and PI orthologs from a number of core eudicots such as Antirrhinum majus, Petunia hybrida, Gerbera hybrida, Solanum lycopersicum, and Nicotiana benthamiana (Sommer et al., 1990; Tröbner et al., 1992; Angenent et al., 1993; van der Krol et al., 1993; Yu et al., 1999; Liu et al., 2004; Vandenbussche et al., 2004; de Martino et al., 2006), from basal eudicot species such as Papaver somniferum and Aquilegia vulgaris (Drea et al., 2007; Kramer et al., 2007), as well as from monocot species such as Zea mays and Oryza sativa (Ambrose et al., 2000; Nagasawa et al., 2003; Prasad and Vijayraghavan, 2003; Yadav et al., 2007; Yao et al., 2008). This indicated that the function of the B class genes AP3 and PI is highly conserved during evolution.It has been thought that B group genes may have arisen from an ancestral gene through multiple gene duplication events (Doyle, 1994; Theißen et al., 1996, 2000; Purugganan, 1997; Kramer et al., 1998; Kramer and Irish, 1999; Lamb and Irish, 2003; Kim et al., 2004; Stellari et al., 2004; Zahn et al., 2005; Hernandez-Hernandez et al., 2007). In the gymnosperms, there was a single putative B class lineage that duplicated to generate the paleoAP3 and PI lineages in angiosperms (Kramer et al., 1998; Theißen et al., 2000; Irish, 2009). The paleoAP3 lineage is composed of AP3 orthologs identified in lower eudicots, magnolid dicots, and monocots (Kramer et al., 1998). Genes in this lineage contain the conserved paleoAP3- and PI-derived motifs in the C-terminal end of the proteins, which have been thought to be characteristics of the B class ancestral gene (Kramer et al., 1998; Tzeng and Yang, 2001; Hsu and Yang, 2002). The PI lineage is composed of PI orthologs that contain a highly conserved PI motif identified in most plant species (Kramer et al., 1998). Subsequently, there was a second duplication at the base of the core eudicots that produced the euAP3 and TM6 lineages, which have been subject to substantial sequence changes in eudicots during evolution (Kramer et al., 1998; Kramer and Irish, 1999). The paleoAP3 motif in the C-terminal end of the proteins was retained in the TM6 lineage and replaced by a conserved euAP3 motif in the euAP3 lineage of most eudicot species (Kramer et al., 1998). In addition, many lineage-specific duplications for paleoAP3 lineage have occurred in plants such as orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009), Ranunculaceae, and Ranunculales (Kramer et al., 2003; Di Stilio et al., 2005; Shan et al., 2006; Kramer, 2009).Unlike the A or C class MADS box proteins, which form homodimers that regulate flower development, the ability of B class proteins to form homodimers has only been reported in gymnosperms and in the paleoAP3 and PI lineages of some monocots. For example, LMADS1 of the lily Lilium longiflorum (Tzeng and Yang, 2001), OMADS3 of the orchid Oncidium Gower Ramsey (Hsu and Yang, 2002), and PeMADS4 of the orchid Phalaenopsis equestris (Tsai et al., 2004) in the paleoAP3 lineage, LRGLOA and LRGLOB of the lily Lilium regale (Winter et al., 2002), TGGLO of the tulip Tulipa gesneriana (Kanno et al., 2003), and PeMADS6 of the orchid P. equestris (Tsai et al., 2005) in the PI lineage, and GGM2 of the gymnosperm Gnetum gnemon (Winter et al., 1999) were able to form homodimers that regulate flower development. Proteins in the euAP3 lineage and in most paleoAP3 lineages were not able to form homodimers and had to interact with PI to form heterodimers in order to regulate petal and stamen development in various plant species (Schwarz-Sommer et al., 1992; Tröbner et al., 1992; Riechmann et al., 1996; Moon et al., 1999; Winter et al., 2002; Kanno et al., 2003; Vandenbussche et al., 2004; Yao et al., 2008). In addition to forming dimers, AP3 and PI were able to interact with other MADS box proteins, such as SEPALLATA1 (SEP1), SEP2, and SEP3, to regulate petal and stamen development (Pelaz et al., 2000; Honma and Goto, 2001; Theißen and Saedler, 2001; Castillejo et al., 2005).Orchids are among the most important plants in the flower market around the world, and research on MADS box genes has been reported for several species of orchids during the past few years (Lu et al., 1993, 2007; Yu and Goh, 2000; Hsu and Yang, 2002; Yu et al., 2002; Hsu et al., 2003; Tsai et al., 2004, 2008; Xu et al., 2006; Guo et al., 2007; Kim et al., 2007; Chang et al., 2009). Unlike the flowers in eudicots, the nearly identical shape of the sepals and petals as well as the production of a unique lip in orchid flowers make them a very special plant species for the study of flower development. Four clades (1–4) of genes in the paleoAP3 lineage have been identified in several orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009). Several works have described the possible interactions among these four clades of paleoAP3 genes and one PI gene that are involved in regulating the differentiation and formation of the sepal/petal/lip of orchids (Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009). However, the exact mechanism that involves the orchid B class genes remains unclear and needs to be clarified by more experimental investigations.O. Gower Ramsey is a popular orchid with important economic value in cut flower markets. Only a few studies have been reported on the role of MADS box genes in regulating flower formation in this plant species (Hsu and Yang, 2002; Hsu et al., 2003; Chang et al., 2009). An AP3-like MADS gene that regulates both floral formation and initiation in transgenic Arabidopsis has been reported (Hsu and Yang, 2002). In addition, four AP1/AGAMOUS-LIKE9 (AGL9)-like MADS box genes have been characterized that show novel expression patterns and cause different effects on floral transition and formation in Arabidopsis (Hsu et al., 2003; Chang et al., 2009). Compared with other orchids, the production of a large and well-expanded lip and five small identical sepals/petals makes O. Gower Ramsey a special case for the study of the diverse functions of B class MADS box genes during evolution. Therefore, the isolation of more B class MADS box genes and further study of their roles in the regulation of perianth (sepal/petal/lip) formation during O. Gower Ramsey flower development are necessary. In addition to the clade 2 paleoAP3 gene OMADS3, which was previously characterized in our laboratory (Hsu and Yang, 2002), three more B class MADS box genes, OMADS5, OMADS8, and OMADS9, were characterized from O. Gower Ramsey in this study. Based on the different expression patterns and the protein interactions among these four orchid B class genes, we propose that the presence of OMADS3/8 and/or OMADS9 is required for sepal/petal/lip formation. Further sepal and petal formation at least requires the additional presence of OMADS5, whereas large lip formation was seen when OMADS5 expression was absent. Our results provide a new finding and information pertaining to the roles for orchid B class MADS box genes in the regulation of sepal/petal/lip formation.     

Calcineurin B-Like Protein-Interacting Protein Kinase CIPK21 Regulates Osmotic and Salt Stress Responses in Arabidopsis

The role of calcium-mediated signaling has been extensively studied in plant responses to abiotic stress signals. Calcineurin B-like proteins (CBLs) and CBL-interacting protein kinases (CIPKs) constitute a complex signaling network acting in diverse plant stress responses. Osmotic stress imposed by soil salinity and drought is a major abiotic stress that impedes plant growth and development and involves calcium-signaling processes. In this study, we report the functional analysis of CIPK21, an Arabidopsis (Arabidopsis thaliana) CBL-interacting protein kinase, ubiquitously expressed in plant tissues and up-regulated under multiple abiotic stress conditions. The growth of a loss-of-function mutant of CIPK21, cipk21, was hypersensitive to high salt and osmotic stress conditions. The calcium sensors CBL2 and CBL3 were found to physically interact with CIPK21 and target this kinase to the tonoplast. Moreover, preferential localization of CIPK21 to the tonoplast was detected under salt stress condition when coexpressed with CBL2 or CBL3. These findings suggest that CIPK21 mediates responses to salt stress condition in Arabidopsis, at least in part, by regulating ion and water homeostasis across the vacuolar membranes.Drought and salinity cause osmotic stress in plants and severely affect crop productivity throughout the world. Plants respond to osmotic stress by changing a number of cellular processes (Xiong et al., 1999; Xiong and Zhu, 2002; Bartels and Sunkar, 2005; Boudsocq and Lauriére, 2005). Some of these changes include activation of stress-responsive genes, regulation of membrane transport at both plasma membrane (PM) and vacuolar membrane (tonoplast) to maintain water and ionic homeostasis, and metabolic changes to produce compatible osmolytes such as Pro (Stewart and Lee, 1974; Krasensky and Jonak, 2012). It has been well established that a specific calcium (Ca²⁺) signature is generated in response to a particular environmental stimulus (Trewavas and Malhó, 1998; Scrase-Field and Knight, 2003; Luan, 2009; Kudla et al., 2010). The Ca²⁺ changes are primarily perceived by several Ca²⁺ sensors such as calmodulin (Reddy, 2001; Luan et al., 2002), Ca²⁺-dependent protein kinases (Harper and Harmon, 2005), calcineurin B-like proteins (CBLs; Luan et al., 2002; Batistič and Kudla, 2004; Pandey, 2008; Luan, 2009; Sanyal et al., 2015), and other Ca²⁺-binding proteins (Reddy, 2001; Shao et al., 2008) to initiate various cellular responses.Plant CBL-type Ca²⁺ sensors interact with and activate CBL-interacting protein kinases (CIPKs) that phosphorylate downstream components to transduce Ca²⁺ signals (Liu et al., 2000; Luan et al., 2002; Batistič and Kudla, 2004; Luan, 2009). In several plant species, multiple members have been identified in the CBL and CIPK family (Luan et al., 2002; Kolukisaoglu et al., 2004; Pandey, 2008; Batistič and Kudla, 2009; Weinl and Kudla, 2009; Pandey et al., 2014). Involvement of specific CBL-CIPK pair to decode a particular type of signal entails the alternative and selective complex formation leading to stimulus-response coupling (D’Angelo et al., 2006; Batistič et al., 2010).Several CBL and CIPK family members have been implicated in plant responses to drought, salinity, and osmotic stress based on genetic analysis of Arabidopsis (Arabidopsis thaliana) mutants (Zhu, 2002; Cheong et al., 2003, 2007; Kim et al., 2003; Pandey et al., 2004, 2008; D’Angelo et al., 2006; Qin et al., 2008; Tripathi et al., 2009; Held et al., 2011; Tang et al., 2012; Drerup et al., 2013; Eckert et al., 2014). A few CIPKs have also been functionally characterized by gain-of-function approach in crop plants such as rice (Oryza sativa), pea (Pisum sativum), and maize (Zea mays) and were found to be involved in osmotic stress responses (Mahajan et al., 2006; Xiang et al., 2007; Yang et al., 2008; Tripathi et al., 2009; Zhao et al., 2009; Cuéllar et al., 2010).In this report, we examined the role of the Arabidopsis CIPK21 gene in osmotic stress response by reverse genetic analysis. The loss-of-function mutant plants became hypersensitive to salt and mannitol stress conditions, suggesting that CIPK21 is involved in the regulation of osmotic stress response in Arabidopsis. These findings are further supported by an enhanced tonoplast targeting of the cytoplasmic CIPK21 through interaction with the vacuolar Ca²⁺ sensors CBL2 and CBL3 under salt stress condition.     

Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.Rational and quantitative assessment of metabolic changes in response to genetic modification (GM) is an open question and in need of innovative solutions. Nontargeted metabolite profiling can detect thousands of compounds, but it is not easy to understand the significance of the changed metabolites in the biochemical and biological context of the organism. To better assess the changes in metabolites from nontargeted metabolomics studies, it is important to examine the changed metabolites in the context of the genome-scale metabolic network of the organism.Metabolomics is a technique that aims to quantify all the metabolites in a biological system (Nikolau and Wurtele, 2007; Nicholson and Lindon, 2008; Roessner and Bowne, 2009). It has been used widely in studies ranging from disease diagnosis (Holmes et al., 2008; DeBerardinis and Thompson, 2012) and drug discovery (Cascante et al., 2002; Kell, 2006) to metabolic reconstruction (Feist et al., 2009; Kim et al., 2012) and metabolic engineering (Keasling, 2010; Lee et al., 2011). Metabolomic studies have demonstrated the possibility of identifying gene functions from changes in the relative concentrations of metabolites (metabotypes or metabolic signatures; Ebbels et al., 2004) in various species including yeast (Saccharomyces cerevisiae; Raamsdonk et al., 2001; Allen et al., 2003), Arabidopsis (Arabidopsis thaliana; Brotman et al., 2011), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Zea mays; Riedelsheimer et al., 2012). Metabolomics has also been used to better understand how plants interact with their environments (Field and Lake, 2011), including their responses to biotic and abiotic stresses (Dixon et al., 2006; Arbona et al., 2013), and to predict important agronomic traits (Riedelsheimer et al., 2012). Metabolite profiling has been performed on many plant species, including angiosperms such as Arabidopsis, poplar (Populus trichocarpa), and Catharanthus roseus (Sumner et al., 2003; Rischer et al., 2006), basal land plants such as Selaginella moellendorffii and Physcomitrella patens (Erxleben et al., 2012; Yobi et al., 2012), and Chlamydomonas reinhardtii (Fernie et al., 2012; Davis et al., 2013). With the availability of whole genome sequences of various species, metabolomics has the potential to become a useful tool for elucidating the functions of genes using large-scale systematic analyses (Fiehn et al., 2000; Saito and Matsuda, 2010; Hur et al., 2013).Although metabolomics data have the potential for identifying the roles of genes that are associated with metabolic phenotypes, the biochemical mechanisms that link functions of genes with metabolic phenotypes are still poorly characterized. For example, we do not yet know the principles behind how perturbing the expression of a single gene changes the metabolic system as a whole. Large-scale metabolomics data have provided useful resources for linking phenotypes to genotypes (Fiehn et al., 2000; Roessner et al., 2001; Tikunov et al., 2005; Schauer et al., 2006; Lu et al., 2011; Fukushima et al., 2014). For example, Lu et al. (2011) compared morphological and metabolic phenotypes from more than 5,000 Arabidopsis chloroplast mutants using gas chromatography (GC)- and liquid chromatography (LC)-mass spectrometry (MS). Fukushima et al. (2014) generated metabolite profiles from various characterized and uncharacterized mutant plants and clustered the mutants with similar metabolic phenotypes by conducting multidimensional scaling with quantified metabolic phenotypes. Nonetheless, representation and analysis of such a large amount of data remains a challenge for scientific discovery (Lu et al., 2011). In addition, these studies do not examine the topological and functional characteristics of metabolic changes in the context of a genome-scale metabolic network. To understand the relationship between genotype and metabolic phenotype, we need to investigate the metabolic changes caused by perturbing the expression of a gene in a genome-scale metabolic network perspective, because metabolic pathways are not independent biochemical factories but are components of a complex network (Berg et al., 2002; Merico et al., 2009).Much progress has been made in the last 2 decades to represent metabolism at a genome scale (Terzer et al., 2009). The advances in genome sequencing and emerging fields such as biocuration and bioinformatics enabled the representation of genome-scale metabolic network reconstructions for model organisms (Bassel et al., 2012). Genome-scale metabolic models have been built and applied broadly from microbes to plants. The first step toward modeling a genome-scale metabolism in a plant species started with developing a genome-scale metabolic pathway database for Arabidopsis (AraCyc; Mueller et al., 2003) from reference pathway databases (Kanehisa and Goto, 2000; Karp et al., 2002; Zhang et al., 2010). Genome-scale metabolic pathway databases have been built for several plant species (Mueller et al., 2005; Zhang et al., 2005, 2010; Urbanczyk-Wochniak and Sumner, 2007; May et al., 2009; Dharmawardhana et al., 2013; Monaco et al., 2013, 2014; Van Moerkercke et al., 2013; Chae et al., 2014; Jung et al., 2014). Efforts have been made to develop predictive genome-scale metabolic models using enzyme kinetics and stoichiometric flux-balance approaches (Sweetlove et al., 2008). de Oliveira Dal’Molin et al. (2010) developed a genome-scale metabolic model for Arabidopsis and successfully validated the model by predicting the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. Other genome-scale models have been developed for Arabidopsis (Poolman et al., 2009; Radrich et al., 2010; Mintz-Oron et al., 2012), C. reinhardtii (Chang et al., 2011; Dal’Molin et al., 2011), maize (Dal’Molin et al., 2010; Saha et al., 2011), sorghum (Sorghum bicolor; Dal’Molin et al., 2010), and sugarcane (Saccharum officinarum; Dal’Molin et al., 2010). These predictive models have the potential to be applied broadly in fields such as metabolic engineering, drug target discovery, identification of gene function, study of evolutionary processes, risk assessment of genetically modified crops, and interpretations of mutant phenotypes (Feist and Palsson, 2008; Ricroch et al., 2011).Here, we interrogate the metabotypes caused by 136 single gene perturbations of Arabidopsis by analyzing the relative concentration changes of 1,348 chemically identified metabolites using a reconstructed genome-scale metabolic network. We examine the characteristics of the changed metabolites (the metabolites whose relative concentrations were significantly different in mutants relative to the wild type) in the metabolic network to uncover biological and topological consequences of the perturbed genes.     

Phosphorylation of the C Terminus of RHD3 Has a Critical Role in Homotypic ER Membrane Fusion in Arabidopsis

The endoplasmic reticulum (ER) consists of dynamically changing tubules and cisternae. In animals and yeast, homotypic ER membrane fusion is mediated by fusogens (atlastin and Sey1p, respectively) that are membrane-associated dynamin-like GTPases. In Arabidopsis (Arabidopsis thaliana), another dynamin-like GTPase, ROOT HAIR DEFECTIVE3 (RHD3), has been proposed as an ER membrane fusogen, but direct evidence is lacking. Here, we show that RHD3 has an ER membrane fusion activity that is enhanced by phosphorylation of its C terminus. The ER network was RHD3-dependently reconstituted from the cytosol and microsome fraction of tobacco (Nicotiana tabacum) cultured cells by exogenously adding GTP, ATP, and F-actin. We next established an in vitro assay system of ER tubule formation with Arabidopsis ER vesicles, in which addition of GTP caused ER sac formation from the ER vesicles. Subsequent application of a shearing force to this system triggered the formation of tubules from the ER sacs in an RHD-dependent manner. Unexpectedly, in the absence of a shearing force, Ser/Thr kinase treatment triggered RHD3-dependent tubule formation. Mass spectrometry showed that RHD3 was phosphorylated at multiple Ser and Thr residues in the C terminus. An antibody against the RHD3 C-terminal peptide abolished kinase-triggered tubule formation. When the Ser cluster was deleted or when the Ser residues were replaced with Ala residues, kinase treatment had no effect on tubule formation. Kinase treatment induced the oligomerization of RHD3. Neither phosphorylation-dependent modulation of membrane fusion nor oligomerization has been reported for atlastin or Sey1p. Taken together, we propose that phosphorylation-stimulated oligomerization of RHD3 enhances ER membrane fusion to form the ER network.In eukaryotic cells, the endoplasmic reticulum (ER) is the organelle with the largest membrane area. The ER consists of an elaborate network of interconnected membrane tubules and cisternae that is continually moving and being remodeled (Friedman and Voeltz, 2011). In plant cells, ER movement and remodeling is primarily driven by the actin-myosin XI cytoskeleton (Sparkes et al., 2009; Ueda et al., 2010; Yokota et al., 2011; Griffing et al., 2014) and secondarily by the microtubule cytoskeleton (Hamada et al., 2014). Several factors involved in creating the ER architecture have been also identified (Anwar et al., 2012; Chen et al., 2012; Goyal and Blackstone, 2013; Sackmann, 2014; Stefano et al., 2014a; Westrate et al., 2015). Among them, ER membrane-bound GTPases, animal atlastins and yeast Sey1p (Synthetic Enhancement of Yop1), function as ER fusogens to form the interconnected tubular network (Hu et al., 2009; Orso et al., 2009; Anwar et al., 2012). Atlastin molecules on the two opposed membranes have been proposed to transiently dimerize to attract the two membranes to each other (Bian et al., 2011; Byrnes and Sondermann, 2011; Morin-Leisk et al., 2011; Moss et al., 2011; Lin et al., 2012; Byrnes et al., 2013). Closely attracted lipid bilayers are supposed to be destabilized by an amphipathic helical domain at the atlastin C terminus to facilitate membrane fusion (Bian et al., 2011; Liu et al., 2012; Faust et al., 2015). Knockdown of atlastins leads to fragmentation of the ER and unbranched ER tubules, while overexpression of atlastins enhances ER membrane fusion, which enlarges the ER profiles (Hu et al., 2009; Orso et al., 2009).An Arabidopsis (Arabidopsis thaliana) protein, ROOT HAIR DEFECTIVE3 (RHD3), has been proposed as a fusogen because (1) when it is disrupted, the ER network is modified into large cable-like strands of poorly branched membranes (Zheng et al., 2004; Chen et al., 2011; Stefano et al., 2012), (2) it shares sequence similarity with the above-mentioned fusogen Sey1p (Hu et al., 2009), and (3) it has structural similarity to atlastin and Sey1p, with a functional GTPase domain at the N-terminal cytosolic domain (Stefano et al., 2012) followed by two transmembrane domains and a cytosolic tail. RHD3 has a longer cytosolic C-terminal tail than do atlastin and Sey1p (Stefano and Brandizzi, 2014). It contains not only an amphipathic region but also a Ser/Thr-rich C terminus.Arabidopsis has two RHD3 isoforms called RHD3-Like 1 and RHD3-Like 2. Fluorescently tagged RHD3 and RHD3-Like 2 localize to the ER (Chen et al., 2011; Stefano et al., 2012; Lee et al., 2013). RHD3 and the two RHD3-Like proteins likely have redundant roles in ER membrane fusion (Zhang et al., 2013). Overexpression of either RHD3 or RHD3-Like 2 with a defective GTPase domain phenocopies the aberrant ER morphology in rhd3-deficient mutants (Chen et al., 2011; Lee et al., 2013).In this study, we show that the Ser/Thr-rich C terminus enhances ER membrane fusion following phosphorylation of its C terminus. We propose a model in which phosphorylation and oligomerization of RHD3 is required for efficient ER membrane fusion. Our findings clarify the mechanisms that regulate RHD3 and consequently the homeostasis of membrane fusion in the ER.     

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.     

Enhanced Abscisic Acid-Mediated Responses in nia1nia2noa1-2 Triple Mutant Impaired in NIA/NR- and AtNOA1-Dependent Nitric Oxide Biosynthesis in Arabidopsis

Nitric oxide (NO) regulates a wide range of plant processes from development to environmental adaptation. Despite its reported regulatory functions, it remains unclear how NO is synthesized in plants. We have generated a triple nia1nia2noa1-2 mutant that is impaired in nitrate reductase (NIA/NR)- and Nitric Oxide-Associated1 (AtNOA1)-mediated NO biosynthetic pathways. NO content in roots of nia1nia2 and noa1-2 plants was lower than in wild-type plants and below the detection limit in nia1nia2noa1-2 plants. NIA/NR- and AtNOA1-mediated biosynthesis of NO were thus active and responsible for most of the NO production in Arabidopsis (Arabidopsis thaliana). The nia1nia2noa1-2 plants displayed reduced size, fertility, and seed germination potential but increased dormancy and resistance to water deficit. The increasing deficiency in NO of nia1nia2, noa1-2, and nia1nia2noa1-2 plants correlated with increased seed dormancy, hypersensitivity to abscisic acid (ABA) in seed germination and establishment, as well as dehydration resistance. In nia1nia2noa1-2 plants, enhanced drought tolerance was due to a very efficient stomata closure and inhibition of opening by ABA, thus uncoupling NO from ABA-triggered responses in NO-deficient guard cells. The NO-deficient mutants in NIA/NR- and AtNOA1-mediated pathways in combination with the triple mutant will be useful tools to functionally characterize the role of NO and the contribution of both biosynthetic pathways in regulating plant development and defense.Nitric oxide (NO) is a small ubiquitous molecule derived from nitrogen-containing precursors that is one of the earliest and most widespread signaling molecules in living organisms from metazoans to mammals (Torreilles, 2001). The regulatory functions of NO have been extensively studied in mammals, where it is synthesized from Arg through the activity of NO synthases (Knowles and Moncada, 1994). By contrast, the biosynthesis and function of this molecule in plants are largely unknown. During the last 10 years, NO biosynthesis in plants has been one of the most controversial topics in plant biology (Durner and Klessig, 1999; Wendehenne et al., 2001; del Río et al., 2004; Zeier et al., 2004; Lamotte et al., 2005; Meyer et al., 2005; Modolo et al., 2005; Crawford, 2006; Crawford et al., 2006; Zemojtel et al., 2006a). Despite the controversy about its biosynthesis, it is now clear that NO regulates many physiological processes of plants, including seed germination, cell death, defense responses against pathogens, stomata function, senescence, and flowering (Beligni and Lamattina, 2000; Pedroso et al., 2000; Neill et al., 2002; Lamattina et al., 2003; He et al., 2004; Romero-Puertas et al., 2004; Wendehenne et al., 2004; Delledonne, 2005; Guo and Crawford, 2005; Simpson, 2005; Grün et al., 2006; Melotto et al., 2006; Planchet et al., 2006; Ali et al., 2007; Mishina et al., 2007).The molecular mechanisms underlying the control of seed dormancy and germination are still poorly characterized. Genetic data support a central role of abscisic acid (ABA) in regulating seed dormancy, whereas gibberellins promote germination (Finkelstein et al., 2008; Holdsworth et al., 2008). In addition, NO has been lately characterized as a new component in the signaling pathway leading to dormancy breakage. NO-releasing compounds reduce dormancy in a NO-dependent manner in Arabidopsis (Arabidopsis thaliana), some warm-season grasses, and certain barley (Hordeum vulgare) cultivars (Bethke et al., 2004; Sarath et al., 2006). More recently, the aleurone layer cells have been characterized as responsive to NO, gibberellins, and ABA, thus becoming a primary determinant of seed dormancy in Arabidopsis (Bethke et al., 2007).Two main enzyme-based pathways have been proposed to be functional for NO biosynthesis in plants. One is based on the activity of nitrate reductases (Meyer et al., 2005; Modolo et al., 2005), and another one, yet undefined, is based on the direct or indirect function of the Nitric Oxide-Associated1/Resistant to Inhibition by Fosfidomycin1 (AtNOA1/RIF1) protein. It has been also reported that NO synthesis from nitrite occurs in mitochondria associated with mitochondrial electron transport (Planchet et al., 2005) and also that this pathway is mainly functioning in roots under anoxia (Gupta et al., 2005). Moreover, the balance between mitochondrial nitrite reduction and superoxide-dependent NO degradation seems to be derived from factors controlling NO levels in Arabidopsis (Wulff et al., 2009). It has been recently reported that the synthesis of NO in floral organs requires nitrate reductase activity (Seligman et al., 2008) and also that homologues of AtNOA1 participate in NO biosynthesis in diatoms (Vardi et al., 2008), mammals (Zemojtel et al., 2006b; Parihar et al., 2008a, 2008b), and Nicotiana benthamiana (Kato et al., 2008). Recently, the identification of the rif1 mutant, carrying a null mutation in the AtNOA1 locus (At3g47450), allowed uncovering of a function for AtNOA1/RIF1 in the expression of plastome-encoded proteins (Flores-Pérez et al., 2008). Moreover, another recent report claims that AtNOA1 is not a NO synthase but a cGTPase (Moreau et al., 2008), likely playing a role in ribosome assembly and subsequent mRNA translation to proteins in the chloroplasts.To date, it is not clear if both pathways coexist in plants and, if so, the corresponding contributions of each pathway to NO biosynthesis. In this work, we have addressed the functions of both pathways in Arabidopsis by generating a triple mutant in both nitrate reductases and AtNOA1 that is severely impaired in NO production. Further characterization of NO-deficient plants allowed us to identify a functional cross talk between NO and ABA in controlling seed germination and dormancy as well as plant resistance to water deficit.