New Evidence for Differential Roles of L10 Ribosomal Proteins from Arabidopsis

The RIBOSOMAL PROTEIN L10 (RPL10) is an integral component of the eukaryotic ribosome large subunit. Besides being a constituent of ribosomes and participating in protein translation, additional extraribosomal functions in the nucleus have been described for RPL10 in different organisms. Previously, we demonstrated that Arabidopsis (Arabidopsis thaliana) RPL10 genes are involved in development and translation under ultraviolet B (UV-B) stress. In this work, transgenic plants expressing Pro_RPL10:β-glucuronidase fusions show that, while AtRPL10A and AtRPL10B are expressed both in the female and male reproductive organs, AtRPL10C expression is restricted to pollen grains. Moreover, the characterization of double rpl10 mutants indicates that the three AtRPL10s differentially contribute to the total RPL10 activity in the male gametophyte. All three AtRPL10 proteins mainly accumulate in the cytosol but also in the nucleus, suggesting extraribosomal functions. After UV-B treatment, only AtRPL10B localization increases in the nuclei. We also here demonstrate that the three AtRPL10 genes can complement a yeast RPL10 mutant. Finally, the involvement of RPL10B and RPL10C in UV-B responses was analyzed by two-dimensional gels followed by mass spectrometry. Overall, our data provide new evidence about the nonredundant roles of RPL10 proteins in Arabidopsis.In eukaryotes, the cytosolic ribosomes consist of large 60S and small 40S subunits. In Arabidopsis (Arabidopsis thaliana), ribosomal protein genes exist as families composed of two to seven members that could be differentially incorporated into the cytosolic ribosome under specific situations (Schmid et al., 2005; Byrne, 2009). In this way, ribosomal heterogeneity would allow selective translation of specific mRNAs under particular cell conditions (Barakat et al., 2001; Szick-Miranda and Bailey-Serres, 2001; Giavalisco et al., 2005; Carroll et al., 2008; Carroll, 2013). Arabidopsis mutants in ribosomal proteins exhibit a large range of developmental phenotypes with extreme abnormalities, including embryonic lethality, suggesting that ribosomes also have specific functions regulating the expression of developmental genes (Van Lijsebettens et al., 1994; Degenhardt and Bonham-Smith, 2008; Byrne, 2009; Horiguchi et al., 2011, 2012; Szakonyi and Byrne, 2011). Furthermore, it has been recently demonstrated that ribosomal proteins control auxin-mediated developmental programs by translational regulation of auxin response factors (Rosado et al., 2012). In addition, the characterization of single, double, and, in certain cases, triple mutants as well as complementation by paralog genes have demonstrated full, partial, and no redundancy between members of ribosomal protein families (Briggs et al., 2006; Guo and Chen, 2008; Guo et al., 2011; Horiguchi et al., 2011; Stirnberg et al., 2012).RIBOSOMAL PROTEIN L10 (RPL10) was initially identified in humans as a putative suppressor of Wilms’ tumor (Dowdy et al., 1991). Since then, RPL10 has been studied in different organisms from archaea and bacteria to eukaryotes such as mammals, insects, yeast, and plants (Marty et al., 1993; Mills et al., 1999; Hwang et al., 2000; Zhang et al., 2004; Wen et al., 2005; Singh et al., 2009). A remarkable property of this protein is its high degree of amino acid conservation, suggesting fundamental and critical conserved functions of RPL10 in different organisms (Farmer et al., 1994; Eisinger et al., 1997; Hofer et al., 2007; Nishimura et al., 2008). Likewise, the crystallographic structural similarity observed among RPL10 orthologs in eukaryotes, bacteria, and archaea (called L16) established the conservation of this universal ribosomal protein family and provided evidence of the inalterability of the ribosome during evolution (Spahn et al., 2001; Nishimura et al., 2008). Nevertheless, besides being a constituent of ribosomes and participating in protein translation, additional extraribosomal functions have been described for RPL10 (Mills et al., 1999; Hwang et al., 2000; Chávez-Rios et al., 2003; Zhang et al., 2004; Singh et al., 2009). In yeast, RPL10 is essential for viability, organizes the union site of the aminoacyl-tRNA, and its incorporation into the 60S subunit is a prerequisite for subunit joining and the initiation of translation (West et al., 2005; Hofer et al., 2007). Extensive analysis of the in vivo assembly of ribosomes revealed that RPL10 is loaded to the ribosome in the cytosol with the assistance of its chaperone suppressor of QSR1 truncations (Hedges et al., 2005; West et al., 2005).Arabidopsis has three genes encoding RPL10 proteins, AtRPL10A, AtRPL10B, and, AtRPL10C. Recently, we demonstrated that Arabidopsis RPL10 genes are differentially regulated by UV-B radiation: RPL10B is down-regulated, RPL10C is up-regulated, while RPL10A is not UV-B regulated. Arabidopsis single mutants showed that RPL10 genes are not functionally equivalent. Heterozygous rpl10a mutant plants are translation deficient under UV-B conditions, knockout rpl10A mutants are not viable, and knockdown homozygous rpl10B mutants show abnormal growth. Conversely, knockout homozygous rpl10C mutants do not exhibit any visible phenotype. Overall, RPL10 genes are involved in development and translation under UV-B stress (Falcone Ferreyra et al., 2010b). Furthermore, coimmunoprecipitation studies showed an association of RPL10 with nuclear proteins, suggesting that at least one of the RPL10 isoforms could have an extraribosomal function in the nucleus (Falcone Ferreyra et al., 2010a).The aim of this work was to further investigate the contribution of each Arabidopsis RPL10 to plant development and UV-B responses. We examined the spatiotemporal expression of each AtRPL10 using transgenic plants expressing Pro_RPL10:GUS fusions. By AtRPL10-GFP fusions, we analyzed the subcellular localization of each RPL10, demonstrating that the three isoforms are mainly localized in the cytosol but also in the nucleus. In order to investigate the functional redundancy between AtRPL10 genes in more detail, we generated and characterized double rpl10 mutants. We also here demonstrate that the three AtRPL10 genes can complement a yeast RPL10 mutant. Finally, the involvement of RPL10B and RPL10C in UV-B responses was analyzed by two-dimensional (2D) gels followed by mass spectrometry. Overall, our data provide new insights into the role of each RPL10 in Arabidopsis.     

Ribosomal Protein RPL27a Promotes Female Gametophyte Development in a Dose-Dependent Manner

Ribosomal protein mutations in Arabidopsis (Arabidopsis thaliana) result in a range of specific developmental phenotypes. Why ribosomal protein mutants have specific phenotypes is not fully known, but such defects potentially result from ribosome insufficiency, ribosome heterogeneity, or extraribosomal functions of ribosomal proteins. Here, we report that ovule development is sensitive to the level of Ribosomal Protein L27a (RPL27a) and is disrupted by mutations in the two paralogs RPL27aC and RPL27aB. Mutations in RPL27aC result in high levels of female sterility, whereas mutations in RPL27aB have a significant but lesser effect on fertility. Progressive reduction in RPL27a function results in increasing sterility, indicating a dose-dependent relationship between RPL27a and female fertility. RPL27a levels in both the sporophyte and gametophyte affect female gametogenesis, with different developmental outcomes determined by the dose of RPL27a. These results demonstrate that RPL27aC and RPL27aB act redundantly and reveal a function for RPL27a in coordinating complex interactions between sporophyte and gametophyte during ovule development.Eukaryotic cytoplasmic ribosomes are comprised of two subunits, a large 60S and a small 40S subunit. The 60S subunit includes 25S or 28S, 5.8S, and 5S ribosomal RNA (rRNA) and approximately 47 ribosomal proteins, whereas the 40S subunit includes an 18S rRNA and approximately 33 ribosomal proteins. In plants and animals, reduced ribosomal protein function results in specific developmental phenotypes (Byrne, 2009; Warner and McIntosh, 2009; McCann and Baserga, 2013; Terzian and Box, 2013; Tsukaya et al., 2013). Currently, it is not known how ribosomal proteins modulate development. Potentially specific developmental phenotypes in ribosomal protein mutants are an outcome of ribosome haploinsufficiency and reduced global protein synthesis or reduced translation of specific proteins. Alternatively, ribosomal proteins, in addition to their role in translation, may have extraribosomal function required for specific developmental processes.In Arabidopsis (Arabidopsis thaliana), cytoplasmic ribosomal proteins are encoded by two to five genes (Barakat et al., 2001; Giavalisco et al., 2005; Carroll et al., 2008). Mutations in single ribosomal protein genes are sometimes gametophyte or embryo lethal (Weijers et al., 2001; Tzafrir et al., 2004). However, many ribosomal protein mutants are viable. These mutants typically display a subtle change in leaf shape and may also have distinct developmental defects affecting embryo morphogenesis, inflorescence development, the transition to flowering, and plant stature (Van Lijsebettens et al., 1994; Ito et al., 2000; Pinon et al., 2008; Yao et al., 2008; Byrne, 2009; Fujikura et al., 2009; Falcone Ferreyra et al., 2010; Rosado et al., 2010; Horiguchi et al., 2011; Szakonyi and Byrne, 2011a, 2011b; Stirnberg et al., 2012). Female fertility is also reduced in several ribosomal protein mutants. Mutations in the ribosomal protein genes SHORT VALVE1 (STV1)/RPL24B, SUPPRESSOR OF ACAULIS52 (SAC52)/RPL10A, ARABIDOPSIS MINUTE-LIKE1 (AML1)/RPS5B, and the Ribosomal Protein L27a gene RPL27aC reduce female fertility (Weijers et al., 2001; Nishimura et al., 2005; Imai et al., 2008; Szakonyi and Byrne, 2011b). aml1 and sac52-t1 are partially and fully gametophyte lethal, respectively. Although lower fertility in stv1 and rpl27ac is associated with defective ovules, the nature of the fertility defect in these mutants has not been fully explored.Female gametophyte development is also disrupted by mutations in a number of genes predicted to be involved in ribosome biogenesis. SLOW WALKER1 (SWA1), SWA3/Arabidopsis thaliana RNA HELICASE36 (AtRH36), and NUCLEOLAR FACTOR1 (NOF1) encode nucleolar-localized proteins required for processing 18S pre-rRNA (Shi et al., 2005; Harscoët et al., 2010; Huang et al., 2010; Liu et al., 2010). Mutations in other genes encoding proteins predicted to be involved in pre-rRNA processing and ribosome maturation or in export of preribosomes from the nucleus to the cytoplasm also reduce female fertility (Li et al., 2009, 2010; Chantha et al., 2010; Wang et al., 2012; Missbach et al., 2013). These mutants share similar phenotypes, where female gametophyte development is delayed and there is a failure in progression through gametophyte mitotic cell divisions. Transmission of these ribosome biogenesis mutants through the female is often reduced. This ostensibly reflects a requirement for active ribosome synthesis and sufficient ribosome levels to support morphogenesis of the gametophyte.Here, we show that mutations in a number of different ribosomal protein genes lead to reduced seed set and an increase in the number of defective ovules in siliques. This is particularly apparent in mutants affecting ribosomal protein RPL27a. We show the two RPL27a genes, RPL27aC and RPL27aB, act redundantly and that ovule development is sensitive to the dose of RPL27a. rpl27ac and rpl27ab mutations are together female and male gametophyte lethal. Single rpl27ac mutants also result in some female gametophyte lethality. In the homozygous rpl27ac-2 mutant, the mature embryo sac is frequently expelled from the ovule, suggesting RPL27a is necessary for maintaining a viable gametophyte. However, in the heterozygous rpl27ac-2/+, gametogenesis frequently fails early in development. This occurs independent of the genotype of the gametophyte, indicating somatic sporophyte cells in the mutant affect gametophyte development. Together, our data demonstrate that appropriate levels of RPL27a in the sporophyte and gametophyte are required for female gametophyte development and plant fertility.     

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.