Focus Issue on Plant Cell Walls: The Arabidopsis Family GT43 Glycosyltransferases Form Two Functionally Nonredundant Groups Essential for the Elongation of Glucuronoxylan Backbone

There exist four members of family GT43 glycosyltransferases in the Arabidopsis (Arabidopsis thaliana) genome, and mutations of two of them, IRX9 and IRX14, have previously been shown to cause a defect in glucuronoxylan (GX) biosynthesis. However, it is currently unknown whether IRX9 and IRX14 perform the same biochemical function and whether the other two GT43 members are also involved in GX biosynthesis. In this report, we performed comprehensive genetic analysis of the functional roles of the four Arabidopsis GT43 members in GX biosynthesis. The I9H (IRX9 homolog) and I14H (IRX14 homolog) genes were shown to be specifically expressed in cells undergoing secondary wall thickening, and their encoded proteins were targeted to the Golgi, where GX is synthesized. Overexpression of I9H but not IRX14 or I14H rescued the GX defects conferred by the irx9 mutation, whereas overexpression of I14H but not IRX9 or I9H complemented the GX defects caused by the irx14 mutation. Double mutant analyses revealed that I9H functioned redundantly with IRX9 and that I14H was redundant with IRX14 in their functions. In addition, double mutations of IRX9 and IRX14 were shown to cause a loss of secondary wall thickening in fibers and a much more severe reduction in GX amount than their single mutants. Together, these results provide genetic evidence demonstrating that all four Arabidopsis GT43 members are involved in GX biosynthesis and suggest that they form two functionally nonredundant groups essential for the normal elongation of GX backbone.Secondary walls constitute the bulk of cellulosic biomass produced by vascular plants. Cellulosic biomass in the form of fibers and wood is an important raw material for a myriad of industrial uses, such as timber, pulping, papermaking, and textiles. Due to the dwindling of nonrenewable fossil fuels and the detrimental effects of burning fossil fuels on the global environment, there has been an urgent call to develop alternative renewable energy sources, and the lignocellulosic biomass from plants is considered to be an attractive renewable source for biofuel production (Somerville, 2006). However, lignocellulosic biomass is recalcitrant to the enzymatic conversion of cellulose into sugars, because cellulose is embedded in a complex mixture of polysaccharides and lignin polymers that block the accessibility of degrading enzymes. It has been shown that reduction of lignin and xylan by chemical or enzymatic treatment or by the transgenic approach reduces the recalcitrance of the lignocellulosic biomass to saccharification (Chen and Dixon, 2007; Himmel et al., 2007; Lee et al., 2009a). Therefore, a complete understanding of how individual components of lignocellulosic biomass are biosynthesized will potentially allow us to design novel strategies for genetic modification of cell wall composition and, hence, reduction in biomass recalcitrance to biofuel production.Xylan is the main hemicellulose that cross-links with cellulose in the secondary walls of dicot plants (Carpita and McCann, 2000). It is made of a linear backbone of β-(1,4)-linked xylosyl residues, about 10% of which are attached with side chains of single residues of glucuronic acid (GlcA) and/or 4-O-methylglucuronic acid (MeGlcA) via α-(1,2)-linkages. The backbone xylosyl residues may also be substituted with the arabinosyl group and acetylated. Based on the nature of the side chains, xylan is generally grouped as (methyl)glucuronoxylan (GX), which is the main hemicellulose in dicots, and arabinoxylan and glucuronoarabinoxylan, which are the most abundant hemicelluloses in grass cell walls (Ebringerová and Heinze, 2000). In addition to the xylosyl backbone, the reducing end of xylan from birch (Betula verrucosa), spruce (Picea abies), Arabidopsis (Arabidopsis thaliana), and poplar (Populus alba × Populus tremula) contains a unique tetrasaccharide sequence β-d-Xylp-(1→3)-α-l-Rhap-(1→2)-α-d-GalpA-(1→4)-d-Xylp (Shimizu et al., 1976; Johansson and Samuelson, 1977; Andersson et al., 1983; Peña et al., 2007; Lee et al., 2009a).The biosynthesis of xylan requires multiple glycosyltransferases and other modifying enzymes. Early biochemical studies revealed the activities of xylosyltransferases, glucuronosyltransferases, arabinosyltransferases, methyltransferases, and acetyltransferases that are likely involved in the biosynthesis of xylan (Baydoun et al., 1983, 1989; Kuroyama and Tsumuraya, 2001; Gregory et al., 2002; Porchia et al., 2002; Urahara et al., 2004; Zeng et al., 2008). However, none of the genes corresponding to these xylan biosynthetic enzymes have been identified. Recent molecular and genetic studies in Arabidopsis and poplar have led to the identification of a number of glycosyltransferases that are essential for GX biosynthesis. Among them, several members of the families GT47 and GT8 from Arabidopsis (FRA8, F8H, IRX8, and PARVUS) and poplar (GT47C, GT8D, and GT8E/8F) are implicated in the biosynthesis of the GX reducing end sequence (Aspeborg et al., 2005; Brown et al., 2005, 2007; Zhong et al., 2005; Zhou et al., 2006, 2007; Lee et al., 2007b, 2009b, 2009c; Peña et al., 2007; Persson et al., 2007). These glycosyltransferase genes are specifically expressed in vessels and fibers, and their encoded proteins are targeted to Golgi, where GX is synthesized, except for PARVUS and GT8E/8F, which are predominantly located in the endoplasmic reticulum (Lee et al., 2007b, 2009c). Mutations of the Arabidopsis FRA8, IRX8, and PARVUS genes all led to a near loss of the reducing end tetrasaccharide sequence and a reduction in GX amount (Brown et al., 2007; Lee et al., 2007b; Peña et al., 2007), indicating their essential roles in the biosynthesis of the GX reducing end sequence, although their exact enzymatic activities are still unknown.The genetic studies have also identified roles of two members of family GT43 glycosyltransferases, IRX9 and IRX14, from Arabidopsis and GT43B from poplar in the biosynthesis of the GX xylosyl backbone (Brown et al., 2007; Peña et al., 2007; Zhou et al., 2007). The expression of IRX9 has been shown to be associated with cells undergoing secondary wall biosynthesis, and its encoded protein is targeted to the Golgi. Mutation of the IRX9 gene causes a drastic reduction in xylan xylosyltransferase activity (Brown et al., 2007; Lee et al., 2007a) and concomitantly a substantial decrease in the GX chain length and GX amount (Peña et al., 2007). Mutation of IRX14 was shown to result in a reduction in the GX level and the xylosyltransferase activity (Brown et al., 2007). In addition, two functionally redundant glycosyltransferases, IRX10 and IRX10-like, which belong to family GT47, were also demonstrated to be required for the normal GX level and xylan xylosyltransferase activity, suggesting their involvement in the biosynthesis of the GX xylosyl backbone (Brown et al., 2009; Wu et al., 2009).In this report, we performed comprehensive molecular and genetic studies of the roles of all members of the Arabidopsis family GT43 glycosyltransferases in GX biosynthesis. We show that, like IRX9, the other three GT43 members, I9H (IRX9 homolog), IRX14, and I14H (IRX14 homolog), are expressed in secondary wall-containing cells and that their encoded proteins are targeted to the Golgi. We have found that the GX defects in the irx9 mutant can be rescued by overexpression of I9H but not IRX14 and I14H. Similarly, overexpression of I14H but not IRX9 and I9H is able to complement the GX defects caused by the irx14 mutation. Furthermore, genetic analysis of an array of double mutants revealed redundant and nonredundant roles of GT43 members in GX biosynthesis. Our findings demonstrate that the Arabidopsis family GT43 glycosyltransferases form two functionally nonredundant groups essential for the normal elongation of GX backbone.     

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.     

Regulation of Microbe-Associated Molecular Pattern-Induced Hypersensitive Cell Death,Phytoalexin Production,and Defense Gene Expression by Calcineurin B-Like Protein-Interacting Protein Kinases,OsCIPK14/15, in Rice Cultured Cells

Although cytosolic free Ca²⁺ mobilization induced by microbe/pathogen-associated molecular patterns is postulated to play a pivotal role in innate immunity in plants, the molecular links between Ca²⁺ and downstream defense responses still remain largely unknown. Calcineurin B-like proteins (CBLs) act as Ca²⁺ sensors to activate specific protein kinases, CBL-interacting protein kinases (CIPKs). We here identified two CIPKs, OsCIPK14 and OsCIPK15, rapidly induced by microbe-associated molecular patterns, including chitooligosaccharides and xylanase (Trichoderma viride/ethylene-inducing xylanase [TvX/EIX]), in rice (Oryza sativa). Although they are located on different chromosomes, they have over 95% nucleotide sequence identity, including the surrounding genomic region, suggesting that they are duplicated genes. OsCIPK14/15 interacted with several OsCBLs through the FISL/NAF motif in yeast cells and showed the strongest interaction with OsCBL4. The recombinant OsCIPK14/15 proteins showed Mn²⁺-dependent protein kinase activity, which was enhanced both by deletion of their FISL/NAF motifs and by combination with OsCBL4. OsCIPK14/15-RNAi transgenic cell lines showed reduced sensitivity to TvX/EIX for the induction of a wide range of defense responses, including hypersensitive cell death, mitochondrial dysfunction, phytoalexin biosynthesis, and pathogenesis-related gene expression. On the other hand, TvX/EIX-induced cell death was enhanced in OsCIPK15-overexpressing lines. Our results suggest that OsCIPK14/15 play a crucial role in the microbe-associated molecular pattern-induced defense signaling pathway in rice cultured cells.Calcium ions regulate diverse cellular processes in plants as a ubiquitous internal second messenger, conveying signals received at the cell surface to the inside of the cell through spatial and temporal concentration changes that are decoded by an array of Ca²⁺ sensors (Reddy, 2001; Sanders et al., 2002; Yang and Poovaiah, 2003). Several families of Ca²⁺ sensors have been identified in higher plants. The best known are calmodulins (CaMs) and CaM-related proteins, which typically contain four EF-hand domains for Ca²⁺ binding (Zielinski, 1998). Unlike mammals, which possess single molecular species of CaM, plants have at least three distinct molecular species of CaM playing diverse physiological functions and whose expression is differently regulated (Yamakawa et al., 2001; Luan et al., 2002; Karita et al., 2004; Takabatake et al., 2007). The second major class is exemplified by the Ca²⁺-dependent protein kinases, which contain CaM-like Ca²⁺-binding domains and a kinase domain in a single protein (Harmon et al., 2000). In addition, a new family of Ca²⁺ sensors was identified as calcineurin B-like (CBL) proteins, which consists of proteins similar to both the regulatory β-subunit of calcineurin and the neuronal Ca²⁺ sensor in animals (Liu and Zhu, 1998; Kudla et al., 1999).Unlike CaMs, which interact with a large variety of target proteins, CBLs specifically target a family of protein kinases referred to as CBL-interacting protein kinases (CIPKs) or SnRK3s (for sucrose nonfermenting 1-related protein kinases type 3), which are most similar to the SNF family protein kinases in yeast (Luan et al., 2002). A database search of the Arabidopsis (Arabidopsis thaliana) genome sequence revealed 10 CBL and 25 CIPK homologues (Luan et al., 2002). Expression patterns of these Ca²⁺ sensors and protein kinases suggest their diverse functions in different signaling processes, including light, hormone, sugar, and stress responses (Batistic and Kudla, 2004). AtCBL4/Salt Overly Sensitive3 (SOS3) and AtCIPK24/SOS2 have been shown to play a key role in Ca²⁺-mediated salt stress adaptation (Zhu, 2002). The CBL-CIPK system has been shown to be involved in signaling pathways of abscisic acid (Kim et al., 2003a), sugar (Gong et al., 2002a), gibberellins (Hwang et al., 2005), salicylic acid (Mahajan et al., 2006), and K⁺ channel regulation (Li et al., 2006; Lee et al., 2007; for review, see Luan, 2009; Batistic and Kudla, 2009). However, physiological functions of most of the family members still remain largely unknown.Plants respond to pathogen attack by activating a variety of defense responses, including the generation of reactive oxygen species (ROS), synthesis of phytoalexins, expression of pathogenesis-related (PR) genes, cell cycle arrest, and mitochondrial dysfunction followed by a form of hypersensitive cell death known as the hypersensitive response (Nürnberger and Scheel, 2001; Greenberg and Yao, 2004; Kadota et al., 2004b). Transient membrane potential changes and Ca²⁺ influx are involved at the initial stage of defense responses (Kuchitsu et al., 1993; Pugin et al., 1997; Blume et al., 2000; Kadota et al., 2004a). Many kinds of defense responses are prevented when Ca²⁺ influx is compromised by Ca²⁺ chelators (Nürnberger and Scheel, 2001; Lecourieux et al., 2002). Since complex spatiotemporal patterns of cytosolic free Ca²⁺ concentration have been suggested to play pivotal roles in defense signaling (Nürnberger and Scheel, 2001; Sanders et al., 2002), multiple Ca²⁺ sensor proteins and their effectors should function in the defense signaling pathways. Although possible involvement of some CaM isoforms (Heo et al., 1999; Yamakawa et al., 2001), Ca²⁺-dependent protein kinases (Romeis et al., 2000, 2001; Ludwig et al., 2005; Kobayashi et al., 2007; Yoshioka et al., 2009), as well as Ca²⁺ regulation of EF-hand-containing enzymes such as ROS-generating NADPH oxidase (Ogasawara et al., 2008) have been suggested, other Ca²⁺-regulated signaling components still remain to be identified. No CBLs or CIPKs have so far been implicated as signaling components in defense signaling.N-Acetylchitooligosaccharides, chitin fragments, are microbe-associated molecular patterns (MAMPs) that are recognized by plasma membrane receptors (Kaku et al., 2006; Miya et al., 2007) and induce a variety of defense responses, such as membrane depolarization (Kuchitsu et al., 1993; Kikuyama et al., 1997), ion fluxes (Kuchitsu et al., 1997), ROS production (Kuchitsu et al., 1995), phytoalexin biosynthesis (Yamada et al., 1993), and induction of PR genes (Nishizawa et al., 1999), without hypersensitive cell death in rice (Oryza sativa) cells. In contrast, a fungal proteinaceous elicitor, xylanase from Trichoderma viride (TvX)/ethylene-inducing xylanase (EIX), which is recognized by two putative plasma membrane receptors, LeEix1 and LeEix2 (Ron and Avni, 2004), triggers hypersensitive cell death along with different kinetics of ROS production and activation of a mitogen-activated protein kinase, OsMPK6, previously named as OsMPK2 or OsMAPK6, in rice cells (Kurusu et al., 2005). These two fungal MAMPs thus provide excellent model systems to study innate immunity in rice cells.This study identified two CIPKs involved in various MAMP-induced layers of defense responses, including PR gene expression, phytoalexin biosynthesis, mitochondrial dysfunction, and cell death, in rice. Molecular characterization of these CIPKs, including interaction with the putative Ca²⁺ sensors as well as their physiological functions, is discussed.