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.     

Cell Type-Specific Gene Expression Analyses by RNA Sequencing Reveal Local High Nitrate-Triggered Lateral Root Initiation in Shoot-Borne Roots of Maize by Modulating Auxin-Related Cell Cycle Regulation

Plants have evolved a unique plasticity of their root system architecture to flexibly exploit heterogeneously distributed mineral elements from soil. Local high concentrations of nitrate trigger lateral root initiation in adult shoot-borne roots of maize (Zea mays) by increasing the frequency of early divisions of phloem pole pericycle cells. Gene expression profiling revealed that, within 12 h of local high nitrate induction, cell cycle activators (cyclin-dependent kinases and cyclin B) were up-regulated, whereas repressors (Kip-related proteins) were down-regulated in the pericycle of shoot-borne roots. In parallel, a ubiquitin protein ligase S-Phase Kinase-Associated Protein1-cullin-F-box protein^{S-Phase Kinase-Associated Protein 2B}-related proteasome pathway participated in cell cycle control. The division of pericycle cells was preceded by increased levels of free indole-3-acetic acid in the stele, resulting in DR5-red fluorescent protein-marked auxin response maxima at the phloem poles. Moreover, laser-capture microdissection-based gene expression analyses indicated that, at the same time, a significant local high nitrate induction of the monocot-specific PIN-FORMED9 gene in phloem pole cells modulated auxin efflux to pericycle cells. Time-dependent gene expression analysis further indicated that local high nitrate availability resulted in PIN-FORMED9-mediated auxin efflux and subsequent cell cycle activation, which culminated in the initiation of lateral root primordia. This study provides unique insights into how adult maize roots translate information on heterogeneous nutrient availability into targeted root developmental responses.Roots have developed adaptive strategies to reprogram their gene expression and metabolic activity in response to heterogeneous soil environments (Osmont et al., 2007). By this way, local environmental stimuli can be integrated into the developmental program of roots (Forde, 2014; Giehl and von Wirén, 2014). In resource-depleted environments, an important heterogeneously distributed soil factor is nutrient availability, which then directs lateral root growth preferentially into nutrient-rich patches (Zhang and Forde, 1998; Lima et al., 2010; Giehl et al., 2012). Such directed lateral root development depends on regulatory networks that integrate both local and systemic signals to coordinate them with the overall plant nutritional status (Ruffel et al., 2011; Guan et al., 2014). As shown by the impact of the N status-dependent regulatory module CLAVATA3/EMBRYO-SURROUNDING REGION-related peptides-CLAVATA1 leucine-rich repeat receptor-like kinase, economizing the costs for root development is pivotal for a resource-efficient strategy in nutrient acquisition (Araya et al., 2014). In recent years, strategies on yield and efficiency improvement have been developed that are primarily based on the manipulation of root system architecture (Gregory et al., 2013; Lynch, 2014; Meister et al., 2014). A common imperative of these strategies is to develop crops that use water and nutrients more efficiently, allowing the reduction of fertilizer input and potentially hazardous environmental contamination.Maize (Zea mays) plays an eminent role in global food, feed, and fuel production, which is also a consequence of its unique root system (Rogers and Benfey, 2015). The genetic analysis of maize root architecture revealed a complex molecular network coordinating root development during the whole lifecycle (for review, see Hochholdinger et al., 2004a, 2004b). Identification of root type-specific lateral root mutants in maize emphasized the existence of regulatory mechanisms involved in the branching of embryonic roots, which are distinct from those in postembryonic roots (Hochholdinger and Feix, 1998; Woll et al., 2005). Under heterogeneous nutrient supplies, nitrate-rich patches increased only the length of lateral roots in primary and seminal roots, whereas they increased both length and density of lateral roots from shoot-borne roots of adult maize plants (Yu et al., 2014a). Remarkably, modulation of the extensive postembryonic shoot-borne root stock has a great potential to improve grain yield and nutrient use efficiency (Hochholdinger and Tuberosa, 2009).Lateral root branching is critical to secure anchorage and ensure adequate uptake of water and nutrients. In maize, these roots originate from concentric single-file layers of pericycle and endodermis cells (Fahn, 1990; Jansen et al., 2012). Lateral root initiation is the result of auxin-dependent cell cycle progression (Beeckman et al., 2001; Jansen et al., 2013a). Most of the molecular changes during the cell cycle like, for instance, the induction of positive regulators, such as cyclins (CYCs) and cyclin-dependent kinases (CDKs), and the repression of Kip-related proteins (KRPs), thus account for a reactivation of the cell cycle (Beeckman et al., 2001; Himanen et al., 2002, 2004). In eukaryotes, ubiquitin-mediated degradation of cell cycle proteins plays a critical role in the regulation of cell division (Hershko, 2005; Jakoby et al., 2006). Conjugation of ubiquitin to a substrate requires the sequential action of three enzymes: ubiquitin-activating enzyme, ubiquitin-conjugating enzyme, and ubiquitin-protein ligase (E3). The E3 enzymes are responsible for the specificity of the pathway, and several classes of E3 enzymes have been implicated in cell cycle regulation, including the S-Phase Kinase-Associated Protein1-cullin-F-box protein (SCF) and Really Interesting New Gene (RING) finger-domain ubiquitin ligases (Del Pozo and Manzano, 2014). The F-box protein S-Phase Kinase-Associated Protein 2B (SKP2B) encodes an F-box ubiquitin ligase, which plays an important role in the cell cycle by regulating the stability of KRP1 and pericycle founder cell division during lateral root initiation (Ren et al., 2008; Manzano et al., 2012).It has been shown that auxin is involved in long-distance signaling to adjust root growth in response to local nutrient availability (Giehl et al., 2012), and it is likely to serve in long-distance signaling for local nutrient responses as well (for review, see Rubio et al., 2009; Krouk et al., 2011; Saini et al., 2013; Forde, 2014). Polar auxin transport is instrumental for the generation of local auxin maxima, which guide these cells to switch their developmental program (Vanneste and Friml, 2009; Lavenus et al., 2013). In Arabidopsis (Arabidopsis thaliana), the PIN-FORMED (PIN) family of auxin efflux carrier proteins controls the directionality of auxin flows to maximum formation at the tip or pericycle cells (Benková et al., 2003; Laskowski et al., 2008; Marhavý et al., 2013). Auxin responses in protoxylem or protophloem cells of the basal meristem coincide with the site of lateral root initiation (De Smet et al., 2007; Jansen et al., 2012). In these defined pericycle cells, the phloem pole pericycle founder cells are primed before auxin accumulation occurs (De Smet et al., 2007; Jansen et al., 2012, 2013a). In contrast to dicots, the larger PIN family in monocots has a more divergent phylogenetic structure (Paponov et al., 2005). It is likely that monocot-specific PIN genes regulate monocot-specific morphogenetic processes, such as the development of a complex root system (Wang et al., 2009; Forestan et al., 2012).The molecular control of lateral root initiation of the root system to heterogeneous nitrate availabilities is not yet understood in maize. In this study, the plasticity of lateral root induction in adult shoot-borne roots of maize in response to local high concentration of nitrate was surveyed in an experimental setup that simulated patchy nitrate distribution. RNA-sequencing (RNA-Seq) experiments and cell type-specific gene expression analyses showed that local nitrate triggers progressive cell cycle control during pericycle cell division. In addition, tissue-specific determination of indole-3-acetic acid (IAA) and its metabolites combined with auxin maxima determination by DR5 supported a role of basipetal auxin transport during lateral root initiation in shoot-borne roots. Thereby, this study provides unique insights in how auxin orchestrates cell cycle control under local nitrate stimulation in the shoot-borne root system of maize.     

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.     

Large-Scale Phosphoprotein Analysis in Medicago truncatula Roots Provides Insight into in Vivo Kinase Activity in Legumes

Nitrogen fixation in legumes requires the development of root organs called nodules and their infection by symbiotic rhizobia. Over the last decade, Medicago truncatula has emerged as a major model plant for the analysis of plant-microbe symbioses and for addressing questions pertaining to legume biology. While the initiation of symbiosis and the development of nitrogen-fixing root nodules depend on the activation of a protein phosphorylation-mediated signal transduction cascade in response to symbiotic signals produced by the rhizobia, few sites of in vivo phosphorylation have previously been identified in M. truncatula. We have characterized sites of phosphorylation on proteins from M. truncatula roots, from both whole cell lysates and membrane-enriched fractions, using immobilized metal affinity chromatography and tandem mass spectrometry. Here, we report 3,457 unique phosphopeptides spanning 3,404 nonredundant sites of in vivo phosphorylation on 829 proteins in M. truncatula Jemalong A17 roots, identified using the complementary tandem mass spectrometry fragmentation methods electron transfer dissociation and collision-activated dissociation. With this being, to our knowledge, the first large-scale plant phosphoproteomic study to utilize electron transfer dissociation, analysis of the identified phosphorylation sites revealed phosphorylation motifs not previously observed in plants. Furthermore, several of the phosphorylation motifs, including LxKxxs and RxxSxxxs, have yet to be reported as kinase specificities for in vivo substrates in any species, to our knowledge. Multiple sites of phosphorylation were identified on several key proteins involved in initiating rhizobial symbiosis, including SICKLE, NUCLEOPORIN133, and INTERACTING PROTEIN OF DMI3. Finally, we used these data to create an open-access online database for M. truncatula phosphoproteomic data.Medicago truncatula has become a model for studying the biology of leguminous plants such as soybean (Glycine max), alfalfa (Medicago sativa), and clover (Trifolium spp.; Singh et al., 2007). Most members of this vast family have the ability to fix atmospheric nitrogen by virtue of an endosymbiotic association with rhizobial bacteria, through which legumes undergo nodulation, the process of forming root nodules (Jones et al., 2007). Legumes are central to modern agriculture and civilization because of their ability to grow in nitrogen-depleted soils and replenish nitrogen through crop rotation. Consequently, there is great interest in understanding the molecular events that allow legumes to recognize their symbionts, develop root nodules, and fix nitrogen. Nod factors are lipochitooligosaccharidic signals secreted by the rhizobia and are required, in most legumes, for intracellular infection and nodule development. In recent decades, an elegant combination of genetics, biochemistry, and cell biology has shown that Nod factors activate intricate signaling events within cells of legume roots, including protein phosphorylation cascades and intracellular ion fluxes (Oldroyd and Downie, 2008).Protein phosphorylation is a central mechanism of signal transfer in cells (Laugesen et al., 2006; Peck, 2006; Huber, 2007). Several characterized protein kinases are required for symbiosis signal transduction in M. truncatula roots (Lévy et al., 2004; Yoshida and Parniske, 2005; Smit et al., 2007). A recent antibody-based study of cultured M. truncatula cells observed protein phosphorylation changes at the proteomic level in response to fungal infection (Trapphoff et al., 2009); however, the target residues of the phosphorylation events were not determined. A variety of studies have determined in vitro phosphorylation sites on legume proteins and demonstrated the biological importance of the target residues by mutagenesis (Yoshida and Parniske, 2005; Arrighi et al., 2006; Lima et al., 2006; Miyahara et al., 2008; Yano et al., 2008). To our knowledge, only six sites of in vivo protein phosphorylation have been detected for M. truncatula (Laugesen et al., 2006; Lima et al., 2006; Wienkoop et al., 2008), demonstrating the need for the identification of endogenous protein phosphorylation sites in legume model organisms on a proteome-wide scale.While considerable advancements have been made in the global analysis of protein phosphorylation (Nita-Lazar et al., 2008; Macek et al., 2009; Piggee, 2009; Thingholm et al., 2009), phosphoproteomics in plants has lagged years behind that of the mammalian systems (Kersten et al., 2006, 2009; Peck, 2006), which have more fully sequenced genomes and better annotated protein predictions. Arabidopsis (Arabidopsis thaliana), the first plant genome sequenced (Arabidopsis Genome Initiative, 2000), is now predicted to have over 1,000 protein kinases (Finn et al., 2008), approximately twice as many as in human (Manning et al., 2002). Because many of the kinases in the commonly studied mammalian systems are not conserved in the plant kingdom, there is significant need for large-scale phosphoproteomic technologies to discern the intricacies of phosphorylation-mediated cell signaling in plants. With the high mass accuracy afforded by the linear ion trap-orbitrap hybrid mass spectrometer (Makarov et al., 2006; Yates et al., 2006), recent studies in Arabidopsis have reported 2,597 phosphopeptides from suspension cell culture (Sugiyama et al., 2008) and 3,029 phosphopeptides from seedlings (Reiland et al., 2009).All previous large-scale plant phosphoproteomic studies have relied solely on collision-activated dissociation (CAD) during tandem mass spectrometry (MS/MS) and have not taken advantage of the more recently developed methods (Kersten et al., 2009) electron capture dissociation (Kelleher et al., 1999) or electron transfer dissociation (ETD; Coon et al., 2004; Syka et al., 2004). Mapping sites of posttranslational modifications, such as phosphorylation, is often more straightforward using electron-based fragmentation methods, as they frequently produce a full spectrum of sequence-informative ions without causing neutral loss of the modifying functional groups (Meng et al., 2005; Chi et al., 2007; Khidekel et al., 2007; Molina et al., 2007; Wiesner et al., 2008; Chalkley et al., 2009; Swaney et al., 2009). With an ETD-enabled hybrid orbitrap mass spectrometer (McAlister et al., 2007, 2008), we previously compared the performance of CAD and ETD tandem MS for large-scale identification of phosphopeptides (Swaney et al., 2009). ETD identified a greater percentage of unique phosphopeptides and more frequently localized phosphorylation sites. Still, the low overlap of identified phosphopeptides indicates that the two methods are highly complementary. With this in mind, we recently developed a decision tree-driven tandem MS algorithm to select the optimal fragmentation method for each precursor (Swaney et al., 2008).Here, we utilize this technology to map sites of in vivo protein phosphorylation in roots of M. truncatula Jemalong A17 plants. Phosphoproteins, from both whole-cell lysate and membrane-enriched fractions, were analyzed after digestion with a variety of different enzymes individually. Utilizing the complementary fragmentation methods of ETD and CAD, we report 3,404 nonredundant phosphorylation sites at an estimated false discovery rate (FDR) of 1%. Analysis of these data revealed several phosphorylation motifs not previously observed in plants. The phosphorylation sites identified provide insight into the potential regulation of key proteins involved in rhizobial symbiosis, potential consensus sequences by which kinases recognize their substrates, and critical phosphorylation events that are conserved between plant species.