In Planta Localization of Stilbenes within Picea abies Phloem

Phenolic stilbene glucosides (astringin, isorhapontin, and piceid) and their aglycons commonly accumulate in the phloem of Norway spruce (Picea abies). However, current knowledge about the localization and accumulation of stilbenes within plant tissues and cells remains limited. Here, we used an innovative combination of novel microanalytical techniques to evaluate stilbenes in a frozen-hydrated condition (i.e. in planta) and a freeze-dried condition across phloem tissues. Semiquantitative time-of-flight secondary ion-mass spectrometry imaging in planta revealed that stilbenes were localized in axial parenchyma cells. Quantitative gas chromatography analysis showed the highest stilbene content in the middle of collapsed phloem with decreases toward the outer phloem. The same trend was detected for soluble sugar and water contents. The specimen water content may affect stilbene composition; the glucoside-to-aglycon ratio decreased slightly with decreases in water content. Phloem chemistry was correlated with three-dimensional structures of phloem as analyzed by microtomography. The outer phloem was characterized by a high volume of empty parenchyma, reduced ray volume, and a large number of axial parenchyma with porous vacuolar contents. Increasing porosity from the inner to the outer phloem was related to decreasing compactness of stilbenes and possible secondary oxidation or polymerization. Our results indicate that aging-dependent changes in phloem may reduce cell functioning, which affects the capacity of the phloem to store water and sugar, and may reduce the defense potential of stilbenes in the axial parenchyma. Our results highlight the power of using a combination of techniques to evaluate tissue- and cell-level mechanisms involved in plant secondary metabolite formation and metabolism.The bark of conifers has anatomically and chemically integrated defense strategies that are either constitutive (i.e. continuously produced) or inducible (i.e. activated as a response to insect or pathogen attack; Krokene, 2015). Many defense traits exist in both forms (Franceschi et al., 2005). For example, axial phloem parenchyma cells (or polyphenolic parenchyma) are critical in conifer bark defense. These cells regularly form in Pinaceae during annual phloem formation (Franceschi et al., 1998, 2000; Krekling et al., 2000; Jyske et al., 2015) but also are produced on invasion (Franceschi et al., 2005; Krokene, 2015). In Norway spruce (Picea abies) phloem, axial parenchyma forms distinctive, continuous tangential sheets across conducting (i.e. noncollapsed) and nonconducting (i.e. collapsed) tissue.Pioneering studies using microscopy with different dye agents and autofluorescence showed that the large vacuole is a special feature of the axial phloem parenchyma that contains phenolic substances (i.e. phenolic bodies; Franceschi et al., 1998). Microscopic imaging techniques also showed that polyphenolic content is highly dynamic (Franceschi et al., 1998, 2000, 2005) and changes seasonally (Krekling et al., 2000). Within the last 5 years, progress in laser microdissection (LMD) has facilitated the sampling of individual tissues and cells, providing information about the exact chemical composition of phenolic content. Li et al. (2012) used LMD to show that the axial parenchyma is the main site of phenolic accumulation in spruce bark, including that of stilbene compounds.Stilbenes are secondary metabolites that are composed of two phenol moieties linked by a C₂ bridge. These compounds are derived from the phenylpropanoid pathway, in which the last steps of biosynthesis are catalyzed by stilbene synthase (Chong et al., 2009). There is increasing interest in these antioxidant, antibacterial, and antiinflammatory compounds for use in healthy human diets, therapeutic approaches, and as protective agents in materials sciences (Shibutani et al., 2004; Metsämuuronen and Siren, 2014; Reinisalo et al., 2015; Hedenström et al., 2016; Sirerol et al., 2016). The tetrahydroxystilbene glucosides trans-astringin (3,3ʹ,4ʹ,5-tetrahydroxystilbene 3-O-β-d-glucoside) and trans-isorhapontin (3,4ʹ,5-trihydroxy-3ʹ-methoxystilbene 3-O-β-d-glucoside) are the most abundant constitutive stilbene compounds of Norway spruce, while the trihydroxystilbene glucoside trans-piceid (resveratrol 3-O-β-glucoside) and stilbene aglycons (i.e. without the sugar moiety) are less abundant. Stilbene synthesis in spruce probably proceeds through the formation of resveratrol (i.e. aglycon of piceid) followed by further modifications (i.e. hydroxylation, O-methylation, and O-glycosylation) to yield tetrahydroxystilbene glucosides (Hammerbacher et al., 2011). Stilbenes are assumed to provide protection against a wide variety of environmental stressors (Franceschi et al., 2005; Witzell and Martin, 2008; Chong et al., 2009). Stilbenes appear to contribute to antifungal defense in spruce (Hammerbacher et al., 2011, 2013). The fungal inoculation of spruce bark with the blue-stain fungus Endoconidiophora polonica (previously named Ceratocystis polonica; de Beer et al., 2014) causes astringin levels to decrease, in parallel with increasing dimeric stilbene glucoside levels in the LMD-isolated axial phloem parenchyma (Li et al., 2012) or increasing levels of corresponding aglycons in bulk tissue (Viiri et al., 2001). During the annual formation of phloem in Norway spruce, the accumulation of stilbene glucosides inside the newest, LMD-isolated phloem ring is preceded by the formation and cellular development of a new band of axial parenchyma (Jyske et al., 2015). These observations strongly indicate that the inducible and constitutive stilbene compounds of spruce phloem are both stored and synthesized in the axial parenchyma.New mass spectrometry imaging techniques provide significant improvements in the mapping of plant metabolites (Briggs and Seah, 1993; Vickerman and Briggs, 2001; Burrell et al., 2007; Cha et al., 2008; Lee et al., 2012; Bjarnholt et al., 2014; Aoki et al., 2016). To elucidate the synthesis, distribution, and metabolism of secondary plant metabolites, it is essential to gather positional information about them in a living state, as pretreatment of specimens, such as drying, may change the distribution and concentration features of soluble chemicals (Metzner et al., 2008; Li et al., 2012; Kuroda et al., 2013). In this study, we used a unique system of time-of-flight secondary ion mass spectrometry and scanning electron microscopy connected with a cryo-shuttle (cryo-TOF-SIMS/SEM) to study the localization and accumulation patterns of stilbenes within cells and tissues of phloem. This system has been developed to study chemical distributions at high-spatial resolution (1 µm) directly from the surfaces of plant specimens in a frozen-hydrated state (i.e. in planta) representing living tissues (Kuroda et al., 2013; Aoki et al., 2016). Time-of-flight secondary ion mass spectrometry (TOF-SIMS) directly detects organic and inorganic compounds on the specimen surface over a broad mass-to-charge ratio (m/z) range by mass spectrometry with high chemical sensitivity. Specimen surface morphology is visualized by the detection of total secondary ion content. The quality of cellular integrity may be further observed by scanning electron microscopy connected with a cryo-shuttle (cryo-SEM) imaging of the frozen surface of the same specimen. The cryo-TOF-SIMS/SEM system has still rarely been applied to the analysis of plant physiology (Metzner et al., 2008, 2010; Iijima et al., 2011; Kuroda et al., 2013; Aoki et al., 2016).Mass spectrometer imaging techniques consist of an ionizer and a mass analyzer. In the TOF-SIMS system, secondary ion mass spectrometry is used as an ionizer and time-of-flight as a mass analyzer. In another mainstream imaging mass spectrometry technique, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), matrix-assisted laser desorption/ionization is used as ionizer. Compared with TOF-SIMS, MALDI-MS is more quantitative and has high-M_r acceptance, but the resolution of MALDI-MS is not high enough for cell-level detection (Aoki et al., 2016). Instead, the spatial resolution of TOF-SIMS is superior to focus on cell functions. The disadvantage of TOF-SIMS is that the ionization and fragmentation phenomenon may be affected by the matrix effect, causing some degree of uncertainty. However, when time-of-flight secondary ion mass spectrometry connected with a cryo-shuttle (cryo-TOF-SIMS) is used in combination with quantitative gas chromatography, it is very powerful to study the positional and temporal distributions of metabolites within living plants.To complement TOF-SIMS analysis, we applied quantitative chemical microanalysis methods to study the amounts of stilbene glucosides and to correlate those with the amounts of total extractives, monosaccharides and disaccharides, and water across phloem and bark. The methods include tangential cryo-sectioning of tissues and their chemical microanalysis by gas chromatography with flame-ionization detection (GC-FID) and gas chromatography-mass spectrometry (GC-MS).To combine the chemical information with phloem morphology, the cellular and subcellular features of the axial phloem parenchyma were analyzed by three-dimensional (3D) synchrotron radiation microtomography (µCT). µCT is a prominent tool that has gained popularity for 3D analysis of xylem structure and physiology (Brodersen, 2013; Cochard et al., 2015), but only recently has it been applied to the 3D analysis of phloem (Jyske et al., 2015). This method offers advantages over traditional light microscopic approaches, as high-throughput data at the submicrometer level can be produced from significantly larger tissue volumes. The data allow for representative volumetric analysis of cellular distributions along with 3D visualization of subcellular features.In this study, we used a novel combination of cutting-edge techniques to analyze in parallel (1) in planta cellular localization and accumulation of stilbene glucosides across phloem and bark by semiquantitative cryo-TOF-SIMS/SEM; (2) tissue-level quantitative amounts of stilbene glucosides, total extractives, and monosaccharides and disaccharides across phloem and bark by tangential cryo-sectioning and GC-FID and GC-MS; (3) 3D cell abundance distributions across phloem and bark by µCT; and (4) variation in water content across phloem and bark (Fig. 1).Open in a separate windowFigure 1.Schematic presentation of the specimen structure and preparation for different analyses. Sample blocks were taken from living tree stem (A) or stem discs (B) at 1.3 m on the stem. The blocks (C) containing outer bark (periderm), phloem, cambium, and part of the outermost xylem ring (D; transverse view of phloem and bark) were further divided into subblocks (1–3; C and E). Subblocks 1 and 2 were quick frozen, and subblock 3 was fixed chemically. Subblock 1 was used for the direct chemical mapping of stilbenes across the phloem from the cambium to the outer bark (i.e. semiquantitative analysis of stilbene localization and accumulation across transverse and radial surfaces [purple] of the tissue block by TOF-SIMS; E-1). To obtain quantitative data on the amounts of stilbenes, other extractives, and carbohydrates across phloem and bark, tangential cryo-sections (250 or 450 µm each; cut slices illustrated with purple in E-2) were cut across subblock 2 and directed for chemical microanalysis by GC-FID (E-2). Subblock 3 was divided into four to six zones, and from each zone, small cuboids (illustrated with purple in E-3) were cut and directed for morphological analysis of phloem by phase-contrast µCT (E-3). Water content across the phloem and bark was analyzed from separate fresh blocks, which were further cut tangentially into thin sections. Black arrows indicate the radial direction from the cambium toward the outer bark. Purple areas show the analyzed locations of each subblock (E). Note that schematic drawings are not to scale.     

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.     

RNA Silencing of Exocyst Genes in the Stigma Impairs the Acceptance of Compatible Pollen in Arabidopsis

Initial pollen-pistil interactions in the Brassicaceae are regulated by rapid communication between pollen grains and stigmatic papillae and are fundamentally important, as they are the first step toward successful fertilization. The goal of this study was to examine the requirement of exocyst subunits, which function in docking secretory vesicles to sites of polarized secretion, in the context of pollen-pistil interactions. One of the exocyst subunit genes, EXO70A1, was previously identified as an essential factor in the stigma for the acceptance of compatible pollen in Arabidopsis (Arabidopsis thaliana) and Brassica napus. We hypothesized that EXO70A1, along with other exocyst subunits, functions in the Brassicaceae dry stigma to deliver cargo-bearing secretory vesicles to the stigmatic papillar plasma membrane, under the pollen attachment site, for pollen hydration and pollen tube entry. Here, we investigated the functions of exocyst complex genes encoding the remaining seven subunits, SECRETORY3 (SEC3), SEC5, SEC6, SEC8, SEC10, SEC15, and EXO84, in Arabidopsis stigmas following compatible pollinations. Stigma-specific RNA-silencing constructs were used to suppress the expression of each exocyst subunit individually. The early postpollination stages of pollen grain adhesion, pollen hydration, pollen tube penetration, seed set, and overall fertility were analyzed in the transgenic lines to evaluate the requirement of each exocyst subunit. Our findings provide comprehensive evidence that all eight exocyst subunits are necessary in the stigma for the acceptance of compatible pollen. Thus, this work implicates a fully functional exocyst complex as a component of the compatible pollen response pathway to promote pollen acceptance.In flowering plants, sexual reproduction occurs as a result of constant communication between the male gametophyte and the female reproductive organ, from the initial acceptance of compatible pollen to final step of successful fertilization (for review, see Beale and Johnson, 2013; Dresselhaus and Franklin-Tong, 2013; Higashiyama and Takeuchi, 2015). In the Brassicaceae, the stigmas that present a receptive surface for pollen are categorized as dry and covered with unicellular papillae (Heslop-Harrison and Shivanna, 1977). Communication is initiated rapidly following contact of a pollen grain with a stigmatic papilla, as the role of the papillae is to regulate the early cellular responses leading to compatible pollen germination. The basal compatible pollen recognition response also presents a barrier to foreign pollen or is inhibited with self-incompatible pollen (for review, see Dickinson, 1995; Hiscock and Allen, 2008; Chapman and Goring, 2010; Indriolo et al., 2014b).The initial adhesive interaction between the pollen grain and the papilla cell in the Brassicaceae is mediated by the exine of the pollen grain and the surface of the stigmatic papilla (Preuss et al., 1993; Zinkl et al., 1999). A stronger connection results between the adhered pollen grain and the stigmatic papilla with the formation of a lipid-protein interface (foot) derived from the pollen coat and the stigmatic papillar surface (Mattson et al., 1974; Stead et al., 1980; Gaude and Dumas, 1986; Elleman and Dickinson, 1990; Elleman et al., 1992; Preuss et al., 1993; Mayfield et al., 2001). It is at this point that a Brassicaceae-specific recognition of compatible pollen is proposed to occur (Hülskamp et al., 1995; Pruitt, 1999), though the nature of this recognition system is not clearly defined. Two stigma-specific Brassica oleracea glycoproteins, the S-Locus Glycoprotein and S-Locus Related1 (SLR1) protein, play a role in compatible pollen adhesion (Luu et al., 1997, 1999), potentially through interactions with the pollen coat proteins, PCP-A1 and SLR1-BP, respectively (Doughty et al., 1998; Takayama et al., 2000). The simultaneous recognition of self-incompatible pollen would also take place at this stage (for review, see Dresselhaus and Franklin-Tong, 2013; Indriolo et al., 2014b; Sawada et al., 2014). Thus, this interface not only provides a strengthened bond between the pollen grain and stigmatic papilla, but likely facilitates the interaction of signaling proteins from both partners to promote specific cellular responses in the stigmatic papilla toward the pollen grain.One response regulated by these interactions is the release of water from the stigmatic papilla to the adhered compatible pollen grain to enable the pollen grain to rehydrate, germinate, and produce a pollen tube (Zuberi and Dickinson, 1985; Preuss et al., 1993). Upon hydration, the pollen tube emerges at the site of pollen-papilla contact and penetrates the stigma surface between the plasma membrane and the overlaying cell wall (Elleman et al., 1992; Kandasamy et al., 1994). Pollen tube entry into the stigmatic surface represents a second barrier, selecting compatible pollen tubes. Subsequently, the compatible pollen tubes traverse down to the base of the stigma, enter the transmitting tract, and grow intracellularly toward ovules for fertilization. Pollen-pistil interactions at these later stages are also highly regulated (for review, see Beale and Johnson, 2013; Dresselhaus and Franklin-Tong, 2013; Higashiyama and Takeuchi, 2015).EXO70A1, a subunit of the exocyst, was identified as a factor involved in early pollen-stigma interactions, where it is required in the stigma for the acceptance of compatible pollen and inhibited by the self-incompatibility response (Samuel et al., 2009). Stigmas from the Arabidopsis (Arabidopsis thaliana) exo70A1 mutant display constitutive rejection of wild-type-compatible pollen (Samuel et al., 2009; Safavian et al., 2014). This stigmatic defect was rescued by the stigma-specific expression of an Red Fluorescent Protein (RFP):EXO70A1 transgene (Samuel et al., 2009) or partially rescued by providing a high relative humidity environment (Safavian et al., 2014). In addition, the stigma-specific expression of an EXO70A1 RNA interference construct in Brassica napus ‘Westar’ resulted in impaired compatible pollen acceptance and a corresponding reduction in seed production compared with compatible pollinations with wild-type B. napus ‘Westar’ pistils (Samuel et al., 2009). From these studies, EXO70A1 was found to be a critical component in stigmatic papillae to promote compatible pollen hydration and pollen tube entry through the stigma surface. One of the functions of the exocyst is to mediate polar secretion (for review, see Heider and Munson, 2012; Zárský et al., 2013; Synek et al., 2014). Consistent with this, previous studies have observed vesicle-like structures in proximity to the stigmatic papillar plasma membrane in response to compatible pollen in both Brassica spp. and Arabidopsis species (Elleman and Dickinson, 1990, 1996; Dickinson, 1995; Safavian and Goring, 2013; Indriolo et al., 2014a). The secretory activity is predicted to promote pollen hydration and pollen tube entry. As well, consistent with the proposed inhibition of EXO70A1 by the self-incompatibility pathway (Samuel et al., 2009), a complete absence or a significant reduction of vesicle-like structures at the stigmatic papillar plasma membrane was observed in the exo70A1 mutant and with self-incompatible pollen (Safavian and Goring, 2013; Indriolo et al., 2014a).The exocyst is a well-defined complex in yeast (Saccharomyces cerevisiae) and animal systems, consisting of eight subunits, SEC3, SEC5, SEC6, SEC8, SEC10, SEC15, EXO70, and EXO84 (TerBush et al., 1996; Guo et al., 1999). Exocyst subunit mutants were first identified in yeast as secretory mutants displaying a cytosolic accumulation of secretory vesicles (Novick et al., 1980). Subsequent work defined roles for the exocyst in vesicle docking at target membranes in processes such as regulated secretion, polarized exocytosis, and cytokinesis to facilitate membrane fusion by Soluble NSF Attachment protein Receptor (SNARE) complexes (for review, see Heider and Munson, 2012; Liu and Guo, 2012). In plants, genes encoding all eight exocyst subunits have been identified, and many of these genes exist as multiple copies. For example, the Arabidopsis genome contains single copy genes for SEC6 and SEC8, two copies each for SECRETORY3 (SEC3), SEC5, SEC10, and SEC15, three EXO84 genes, and 23 EXO70 genes (Chong et al., 2010; Cvrčková et al., 2012; Vukašinović et al., 2014). Ultrastructural studies using electron tomography uncovered the existence of a structure resembling the exocyst in Arabidopsis (Otegui and Staehelin, 2004; Seguí-Simarro et al., 2004). Localization studies of specific Arabidopsis exocyst subunits also supported conserved roles in polarized exocytosis and cytokinesis in plants. Localization studies have shown EXO70, SEC6, and SEC8 at the growing tip of pollen tubes (Hála et al., 2008), EXO70A1 at the stigmatic papillar plasma membrane (Samuel et al., 2009), SEC3a, SEC6, SEC8, SEC15b, EXO70A1, and EXO84b at the root epidermal cell plasma membrane and developing cell plate (Fendrych et al., 2010, 2013; Wu et al., 2013; Zhang et al., 2013; Rybak et al., 2014), and SEC3a at the plasma membrane in the embryo and root hair (Zhang et al., 2013). Similar to the yeast exocyst mutants, vesicle accumulation has also been observed in the exo70A1 and exo84b mutants (Fendrych et al., 2010; Safavian and Goring, 2013). Taken together, these findings strongly support that plant exocyst subunits function in vivo in vesicle docking at sites of polarized secretion and cytokinesis (for review, see Zárský et al., 2013). In support of this, a recent study investigating Transport Protein Particle (TRAPP)II and exocyst complexes during cytokinesis in Arabidopsis has identified all eight exocyst components in immunoprecipitated complexes (SEC3a/SEC3b, SEC5a, SEC6, SEC8, SEC10, SEC15b, EXO70A1, EXO70H2, and EXO84b; Rybak et al., 2014).Several plant exocyst subunit genes have been implicated in biological processes that rely on regulated vesicle trafficking, where corresponding mutants have displayed a range of growth defects. At the cellular level, these phenotypes have been associated with decreased cell elongation and polar growth (Cole et al., 2005, 2014; Wen et al., 2005; Synek et al., 2006), defects in cytokinesis and cell plate formation (Fendrych et al., 2010; Wu et al., 2013; Rybak et al., 2014), and disrupted Pin-Formed (PIN) auxin efflux carrier recycling and polar auxin transport (Drdová et al., 2013). Several Arabidopsis subunit mutants display strong growth defects such as the sec3a mutant with an embryo-lethal phenotype (Zhang et al., 2013), sec6, sec8, and exo84b mutants with severely dwarfed phenotypes and defects in root growth (Fendrych et al., 2010; Wu et al., 2013; Cole et al., 2014), and exo70A1 with a milder dwarf phenotype (Synek et al., 2006). The Arabidopsis exo70A1 mutant has also been reported to have defects in root hair elongation, hypocotyl elongation, compatible pollen acceptance, seed coat deposition, and tracheary element differentiation (Synek et al., 2006; Samuel et al., 2009; Kulich et al., 2010; Li et al., 2013). Essential roles for other exocyst subunits include Arabidopsis SEC5a/SEC5b, SEC6, SEC8, and SEC15a/SEC15b in male gametophyte development and pollen tube growth (Cole et al., 2005; Hála et al., 2008; Wu et al., 2013), SEC8 in seed coat deposition (Kulich et al., 2010), SEC5a, SEC8, EXO70A1, and EXO84b in root meristem size and root cell elongation (Cole et al., 2014), and a maize (Zea mays) SEC3 homolog in root hair elongation (Wen et al., 2005). Finally, the Arabidopsis EXO70B1, EXO70B2, and EXO70H1 subunits have been implicated in plant defense responses (Pecenková et al., 2011; Stegmann et al., 2012; Kulich et al., 2013; Stegmann et al., 2013).Even with these detailed studies on the functions of exocyst subunits in plants, a systematic demonstration of the requirement of all eight exocyst subunits in a specific plant biological process is currently lacking. EXO70A1 was previously identified as an essential factor in the stigma for compatible pollen-pistil interactions in Arabidopsis and B. napus (Samuel et al., 2009), and we hypothesized that this protein functions as part of the exocyst complex to tether post-Golgi secretory vesicles to stigmatic papillar plasma membrane (Safavian and Goring, 2013). To provide support for the proposed biological role of the exocyst in the stigma for compatible pollen acceptance, we investigated the roles of the remaining seven subunits, SEC3, SEC5, SEC6, SEC8, SEC10, SEC15, and EXO84, in Arabidopsis stigmatic papillae. Given that some Arabidopsis exocyst subunits were previously determined to be essential at earlier growth stages, stigma-specific RNA-silencing constructs were used for each exocyst subunit, and the early postpollination stages were analyzed for these transgenic lines. Our collective data demonstrates that all eight exocyst subunits are required in the stigma for the early stages of compatible pollen-pistil interactions.