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.     

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.     

A Host RNA Helicase-Like Protein,AtRH8, Interacts with the Potyviral Genome-Linked Protein,VPg, Associates with the Virus Accumulation Complex,and Is Essential for Infection

The viral genome-linked protein, VPg, of potyviruses is a multifunctional protein involved in viral genome translation and replication. Previous studies have shown that both eukaryotic translation initiation factor 4E (eIF4E) and eIF4G or their respective isoforms from the eIF4F complex, which modulates the initiation of protein translation, selectively interact with VPg and are required for potyvirus infection. Here, we report the identification of two DEAD-box RNA helicase-like proteins, PpDDXL and AtRH8 from peach (Prunus persica) and Arabidopsis (Arabidopsis thaliana), respectively, both interacting with VPg. We show that AtRH8 is dispensable for plant growth and development but necessary for potyvirus infection. In potyvirus-infected Nicotiana benthamiana leaf tissues, AtRH8 colocalizes with the chloroplast-bound virus accumulation vesicles, suggesting a possible role of AtRH8 in viral genome translation and replication. Deletion analyses of AtRH8 have identified the VPg-binding region. Comparison of this region and the corresponding region of PpDDXL suggests that they are highly conserved and share the same secondary structure. Moreover, overexpression of the VPg-binding region from either AtRH8 or PpDDXL suppresses potyvirus accumulation in infected N. benthamiana leaf tissues. Taken together, these data demonstrate that AtRH8, interacting with VPg, is a host factor required for the potyvirus infection process and that both AtRH8 and PpDDXL may be manipulated for the development of genetic resistance against potyvirus infections.Plant viruses are obligate intracellular parasites that infect many agriculturally important crops and cause severe losses each year. One of the common characteristics of plant viruses is their relatively small genome that encodes a limited number of viral proteins, making them dependent on host factors to fulfill their infection cycles (Maule et al., 2002; Whitham and Wang, 2004; Nelson and Citovsky, 2005; Decroocq et al., 2006). In order to establish a successful infection, the invading virus must recruit an array of host proteins (host factors) to translate and replicate its genome and to move locally from cell to cell via the plasmodesmata and systemically via the vascular system. It has been suggested that down-regulation or mutation of some of the required host factors may result in recessively inherited resistance to viruses (Kang et al., 2005b).Potyviruses, belonging to the genus Potyvirus in the family Potyviradae, constitute the largest group of plant viruses (Rajamäki et al., 2004). Potyviruses have a single positive-strand RNA genome approximately 10 kb in length, with a viral genome-linked protein (VPg) covalently attached to the 5′ end and a poly(A) tail at the 3′ end (Urcuqui-Inchima et al., 2001; Rajamäki et al., 2004). The viral genome contains a single open reading frame (ORF) that translates into a polypeptide with a molecular mass of approximately 350 kD, which is cleaved into 10 mature proteins by viral proteases (Urcuqui-Inchima et al., 2001). Recently, a novel viral protein resulting from a frameshift in the P3 cistron has been reported (Chung et al., 2008). Of the 11 viral proteins, VPg is a multifunctional protein and the only other viral protein present in the viral particles (virions) besides the coat protein and the cylindrical inclusion protein (CI; Oruetxebarria et al., 2001; Puustinen et al., 2002; Gabrenaite-Verkhovskaya et al., 2008). The nonstructural protein is linked to the viral RNA by a phosphodiester bond between the 5′ terminal uridine residue of the RNA and the O⁴-hydroxyl group of amino acid Tyr (Murphy et al., 1996; Oruetxebarria et al., 2001; Puustinen et al., 2002). Mutation of the Tyr residue that links VPg to the viral RNA abolishes virus infectivity completely (Murphy et al., 1996). In infected cells, VPg and its precursor NIa are present in the nucleus and in the membrane-associated virus replication vesicles in the cytoplasm (Carrington et al., 1993; Rajamäki and Valkonen, 2003; Cotton et al., 2009). As a component of the replication complex, VPg may serve as a primer for viral RNA replication (Puustinen and Mäkinen, 2004) and as an analog of the m⁷G cap of mRNAs for the viral genome to recruit the translation complex for translation (Michon et al., 2006; Beauchemin et al., 2007; Khan et al., 2008). Furthermore, VPg has been suggested to be an avirulence factor for recessive resistance genes in diverse plant species (Moury et al., 2004; Kang et al., 2005b; Bruun-Rasmussen et al., 2007). Thus, VPg plays a pivotal role in the virus infection process. The molecular identification of VPg-interacting host proteins and the subsequent functional characterization of such interactions may advance knowledge of the intricate virus replication mechanisms and help develop novel antiviral strategies.Previous studies have shown that VPg and its precursor NIa interact with several host proteins, including three essential components of the host protein translation apparatus (Thivierge et al., 2008). The first protein is the cellular translation initiation factor eIF4E or its isoform eIF(iso)4E, identified through a yeast two-hybrid screen using VPg as a bait (Wittmann et al., 1997; Schaad et al., 2000). The protein complex of VPg and eIF4E is an essential component for virus infectivity (Robaglia and Caranta, 2006). Mutations and knockout of eIF4E or eIF(iso)4E confer resistance to infection (Lellis et al., 2002; Ruffel et al., 2002; Nicaise et al., 2003; Gao et al., 2004; Kang et al., 2005a; Ruffel et al., 2005; Decroocq et al., 2006; Bruun-Rasmussen et al., 2007). It is well known that potyviruses recruit selectively one of the eIF4E isoforms, depending on specific virus-host combinations (German-Retana et al., 2008). For instance, in Arabidopsis (Arabidopsis thaliana), eIF(iso)4E is required for infection by Turnip mosaic virus (TuMV), Plum pox virus (PPV), and Lettuce mosaic virus, while eIF4E is indispensable for infection by Clover yellow vein virus (Duprat et al., 2002; Lellis et al., 2002; Sato et al., 2005; Decroocq et al., 2006). The second cellular protein interacting with VPg is another translation initiation factor, eIF4G. Analysis of Arabidopsis knockout mutants for eIF4G or its isomers eIF(iso)4G1 and eIF(iso)4G2 has yielded results supporting the idea that the recruitment of eIF4G for potyvirus infection is also isoform dependent (Nicaise et al., 2007). Recently, poly(A)-binding protein (PABP), the translation initiation factor that bridges the 5′ and 3′ termini of the mRNA into proximity, has been proposed to be essential for efficient multiplication of TuMV (Dufresne et al., 2008). PABP was previously documented to interact with NIa, a VPg precursor containing both VPg and the proteinase NIa-Pro (Léonard et al., 2004). As the translation factors eIF(iso)4E and PABP have been found to be internalized in virus-induced vesicles, it has been suggested that the interactions between VPg and these translation factors are crucial for viral RNA translation and/or replication (Beauchemin and Laliberté, 2007; Beauchemin et al., 2007; Cotton et al., 2009). Besides these three translation factors, a Cys-rich plant protein, potyvirus VPg-interaction protein, was also found to associate with VPg (Dunoyer et al., 2004). This plant-specific VPg-interacting host protein contains a PHD finger domain and acts as an ancillary factor to support potyvirus infection and movement (Dunoyer et al., 2004).In this study, we describe the identification of an Arabidopsis DEAD-box RNA helicase (DDX), AtRH8, and a peach (Prunus persica) DDX-like protein, PpDDXL, both interacting with the potyviral VPg protein. Using the atrh8 mutant, we demonstrate that AtRH8 is not required for plant growth and development in Arabidopsis but is necessary for infection by two plant potyviruses, PPV and TuMV. Furthermore, we present evidence that AtRH8 colocalizes with the virus accumulation complex in potyvirus-infected leaf tissues, which reveals a possible role of AtRH8 in virus infection. Finally, we have identified the VPg-binding region (VPg-BR) of AtRH8 and PpDDX and show that overexpression of the VPg-BR either from AtRH8 or PpDDXL suppresses virus accumulation.     

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.     

Extra-Large G Proteins Expand the Repertoire of Subunits in Arabidopsis Heterotrimeric G Protein Signaling

Heterotrimeric G proteins, consisting of Gα, Gβ, and Gγ subunits, are a conserved signal transduction mechanism in eukaryotes. However, G protein subunit numbers in diploid plant genomes are greatly reduced as compared with animals and do not correlate with the diversity of functions and phenotypes in which heterotrimeric G proteins have been implicated. In addition to GPA1, the sole canonical Arabidopsis (Arabidopsis thaliana) Gα subunit, Arabidopsis has three related proteins: the extra-large GTP-binding proteins XLG1, XLG2, and XLG3. We demonstrate that the XLGs can bind Gβγ dimers (AGB1 plus a Gγ subunit: AGG1, AGG2, or AGG3) with differing specificity in yeast (Saccharomyces cerevisiae) three-hybrid assays. Our in silico structural analysis shows that XLG3 aligns closely to the crystal structure of GPA1, and XLG3 also competes with GPA1 for Gβγ binding in yeast. We observed interaction of the XLGs with all three Gβγ dimers at the plasma membrane in planta by bimolecular fluorescence complementation. Bioinformatic and localization studies identified and confirmed nuclear localization signals in XLG2 and XLG3 and a nuclear export signal in XLG3, which may facilitate intracellular shuttling. We found that tunicamycin, salt, and glucose hypersensitivity and increased stomatal density are agb1-specific phenotypes that are not observed in gpa1 mutants but are recapitulated in xlg mutants. Thus, XLG-Gβγ heterotrimers provide additional signaling modalities for tuning plant G protein responses and increase the repertoire of G protein heterotrimer combinations from three to 12. The potential for signal partitioning and competition between the XLGs and GPA1 is a new paradigm for plant-specific cell signaling.The classical heterotrimeric G protein consists of a GDP/GTP-binding Gα subunit with GTPase activity bound to an obligate dimer formed by Gβ and Gγ subunits. In the signaling paradigm largely elucidated from mammalian systems, the plasma membrane-associated heterotrimer contains Gα in its GDP-bound form. Upon receiving a molecular signal, typically transduced by a transmembrane protein (e.g. a G protein-coupled receptor), Gα exchanges GDP for GTP and dissociates from the Gβγ dimer. Both Gα and Gβγ interact with intracellular effectors to initiate downstream signaling cascades. The intrinsic GTPase activity of Gα restores Gα to the GDP-bound form, which binds Gβγ, thereby reconstituting the heterotrimer (McCudden et al., 2005; Oldham and Hamm, 2008).Signal transduction through a heterotrimeric G protein complex is an evolutionarily conserved eukaryotic mechanism common to metazoa and plants, although there are distinct differences in the functional intricacies between the evolutionary branches (Jones et al., 2011a, 2011b; Bradford et al., 2013). The numbers of each subunit encoded within genomes, and therefore the potential for combinatorial complexity within the heterotrimer, is one of the most striking differences between plants and animals. For example, the human genome encodes 23 Gα (encoded by 16 genes), five Gβ, and 12 Gγ subunits (Hurowitz et al., 2000; McCudden et al., 2005; Birnbaumer, 2007). The Arabidopsis (Arabidopsis thaliana) genome, however, only encodes one canonical Gα (GPA1; Ma et al., 1990), one Gβ (AGB1; Weiss et al., 1994), and three Gγ (AGG1, AGG2, and AGG3) subunits (Mason and Botella, 2000, 2001; Chakravorty et al., 2011), while the rice (Oryza sativa) genome encodes one Gα (Ishikawa et al., 1995), one Gβ (Ishikawa et al., 1996), and either four or five Gγ subunits (Kato et al., 2004; Chakravorty et al., 2011; Botella, 2012). As expected, genomes of polyploid plants have more copies due to genome duplication, with the soybean (Glycine max) genome encoding four Gα, four Gβ (Bisht et al., 2011), and 10 Gγ subunits (Choudhury et al., 2011). However, Arabidopsis heterotrimeric G proteins have been implicated in a surprisingly large number of phenotypes, which is seemingly contradictory given the relative scarcity of subunits. Arabidopsis G proteins have been implicated in cell division (Ullah et al., 2001; Chen et al., 2006) and morphological development in various tissues, including hypocotyls (Ullah et al., 2001, 2003), roots (Ullah et al., 2003; Chen et al., 2006; Li et al., 2012), leaves (Lease et al., 2001; Ullah et al., 2001), inflorescences (Ullah et al., 2003), and flowers and siliques (Lease et al., 2001), as well as in pathogen responses (Llorente et al., 2005; Trusov et al., 2006; Cheng et al., 2015), regulation of stomatal movement (Wang et al., 2001; Coursol et al., 2003; Fan et al., 2008) and development (Zhang et al., 2008; Nilson and Assmann, 2010), cell wall composition (Delgado-Cerezo et al., 2012), responses to various light stimuli (Warpeha et al., 2007; Botto et al., 2009), responses to multiple abiotic stimuli (Huang et al., 2006; Pandey et al., 2006; Trusov et al., 2007; Zhang et al., 2008; Colaneri et al., 2014), responses to various hormones during germination (Ullah et al., 2002), and postgermination development (Ullah et al., 2002; Pandey et al., 2006; Trusov et al., 2007). Since the Gγ subunit appeared to be the only subunit that provides diversity in heterotrimer composition in Arabidopsis, it was proposed that all functional specificity in heterotrimeric G protein signaling was provided by the Gγ subunit (Trusov et al., 2007; Chakravorty et al., 2011; Thung et al., 2012, 2013). This allowed for only three heterotrimer combinations to account for the wide range of G protein-associated phenotypes.In addition to the above typical G protein subunits, the plant kingdom contains a conserved protein family of extra-large GTP-binding proteins (XLGs). XLGs differ from typical Gα subunits in that they possess a long N-terminal extension of unknown function, but they are similar in that they all have a typical C-terminal Gα-like region, with five semiconserved G-box (G1–G5) motifs. The XLGs also possess the two sequence features that differentiate heterotrimeric G protein Gα subunits from monomeric G proteins: a helical region between the G1 and G2 motifs and an Asp/Glu-rich loop between the G3 and G4 motifs (Lee and Assmann, 1999; Ding et al., 2008; Heo et al., 2012). The Arabidopsis XLG family comprises XLG1, XLG2, and XLG3, and all three have demonstrated GTP-binding and GTPase activities, although they differ from GPA1 in exhibiting a much slower rate of GTP hydrolysis, with a Ca²⁺ cofactor requirement instead of an Mg²⁺ requirement, as for canonical Gα proteins (Heo et al., 2012). All three Arabidopsis XLGs were observed to be nuclear localized (Ding et al., 2008). Although much less is known about XLGs than canonical Gα subunits, XLG2 positively regulates resistance to the bacterial pathogen Pseudomonas syringae and was immunoprecipitated with AGB1 from tissue infected with P. syringae (Zhu et al., 2009). xlg3 mutants, like agb1 mutants, are impaired in root-waving and root-skewing responses (Pandey et al., 2008). During the preparation of this report, Maruta et al. (2015) further investigated XLG2, particularly focusing on the link between XLG2 and Gβγ in pathogen responses. Based on symptom progression in xlg mutants, they found that XLG2 is a positive regulator of resistance to both bacterial and fungal pathogens, with a minor contribution from XLG3 in resistance to Fusarium oxysporum. XLG2 and XLG3 are also positive regulators of reactive oxygen species (ROS) production in response to pathogen-associated molecular pattern elicitors. The resistance and pathogen-associated molecular pattern-induced ROS phenotypes of the agg1 agg2 and xlg2 xlg3 double mutants were not additive in an agg1 agg2 xlg2 xlg3 quadruple mutant, indicating that these two XLGs and the two Gγ subunits function in the same, rather than parallel, pathways. Unfortunately, the close proximity of XLG2 and AGB1 on chromosome 4 precluded the generation of an agb1 xlg2 double mutant; therefore, direct genetic evidence of XLG2 and AGB1 interaction is still lacking, but physical interactions between XLG2 and the Gβγ dimers were shown by yeast (Saccharomyces cerevisiae) three-hybrid and bimolecular fluorescence complementation (BiFC) assays (Maruta et al., 2015). Localization of all three XLGs was also reexamined, indicating that XLGs are capable of localizing to the plasma membrane in addition to the nucleus (Maruta et al., 2015).Interestingly, several other plant G protein-related phenotypes, in addition to pathogen resistance, have been observed only in Gβ and Gγ mutants, with opposite phenotypes observed in Gα (gpa1) mutants. Traditionally, the observation of opposite phenotypes in Gα versus Gβγ mutants in plants and other organisms has mechanistically been attributed to signaling mediated by free Gβγ, which increases in abundance in the absence of Gα. However, an intriguing alternative is that XLG proteins fulfill a Gα-like role in forming heterotrimeric complexes with Gβγ and function in non-GPA1-based G protein signaling processes. If XLGs function like Gα subunits, the corresponding increase in subunit diversity could potentially account for the diversity of G protein phenotypes. In light of this possibility, we assessed the heterotrimerization potential of all possible XLG and Gβγ dimer combinations, XLG localization and its regulation by Gβγ, and the effect of xlg mutation on selected known phenotypes associated with heterotrimeric G proteins. Our results provide compelling evidence for the formation of XLG-Gβγ heterotrimers and reveal that plant G protein signaling is substantially more complex than previously thought.     

Hydrophobin Fusions for High-Level Transient Protein Expression and Purification in Nicotiana benthamiana

Insufficient accumulation levels of recombinant proteins in plants and the lack of efficient purification methods for recovering these valuable proteins have hindered the development of plant biotechnology applications. Hydrophobins are small and surface-active proteins derived from filamentous fungi that can be easily purified by a surfactant-based aqueous two-phase system. In this study, the hydrophobin HFBI sequence from Trichoderma reesei was fused to green fluorescent protein (GFP) and transiently expressed in Nicotiana benthamiana plants by Agrobacterium tumefaciens infiltration. The HFBI fusion significantly enhanced the accumulation of GFP, with the concentration of the fusion protein reaching 51% of total soluble protein, while also delaying necrosis of the infiltrated leaves. Furthermore, the endoplasmic reticulum-targeted GFP-HFBI fusion induced the formation of large novel protein bodies. A simple and scalable surfactant-based aqueous two-phase system was optimized to recover the HFBI fusion proteins from leaf extracts. The single-step phase separation was able to selectively recover up to 91% of the GFP-HFBI up to concentrations of 10 mg mL⁻¹. HFBI fusions increased the expression levels of plant-made recombinant proteins while also providing a simple means for their subsequent purification. This hydrophobin fusion technology, when combined with the speed and posttranslational modification capabilities of plants, enhances the value of transient plant-based expression systems.As the amount of plant genome and proteome information increases, the need has arisen to develop technologies to rapidly overexpress these genes and to characterize the proteins at the structural and functional levels. Based on two decades of research, plant expression platforms are now recognized as a safe, effective, and inexpensive means of producing heterologous recombinant proteins (Ma et al., 2003).Agroinfiltration in Nicotiana benthamiana leaves (Kapila et al., 1997; Yang et al., 2000), when combined with the coexpression of a suppressor of gene silencing (Silhavy et al., 2002; Voinnet et al., 2003), has established itself as the most utilized transient expression system in plants. Agroinfiltration is a fast and convenient technique, producing recombinant protein within 2 to 5 d. This transient expression system is also flexible, as it allows for the expression of multiple genes simultaneously (Johansen and Carrington, 2001) and the transfer of relatively large genes (greater than 2 kb), which are genetically unstable in viral vectors (Porta and Lomonossoff, 1996). Although typically used for preliminary laboratory-scale analyses, agroinfiltration is now being scaled up for the rapid production of gram quantities of recombinant proteins in plants (Vézina et al., 2009).Despite the success of plant expression systems, two major challenges still limiting the economical production of plant-made recombinant proteins include inadequate accumulation levels and the lack of efficient purification methods. Thus, several protein fusion strategies have been developed to address these issues (Terpe, 2003). For example, the use of protein-stabilizing fusion partners, such as ubiquitin (Garbarino et al., 1995; Hondred et al., 1999; Mishra et al., 2006), β-glucuronidase (Gil et al., 2001; Dus Santos et al., 2002), cholera toxin B subunit (Arakawa et al., 2001; Kim et al., 2004; Molina et al., 2004), viral coat proteins (Canizares et al., 2005), and human IgG α-chains (Obregon et al., 2006), are common approaches for enhancing recombinant protein accumulation in plants. To simplify purification, recombinant proteins are often fused translationally to small affinity tags or proteins with defined binding characteristics, such as the StrepII tag, Arg tag, His tag, FLAG tag, c-myc tag, glutathione S-transferase tag, calmodulin-binding peptide, maltose-binding protein, and cellulose-binding domain (Terpe, 2003; Witte et al., 2004; Lichty et al., 2005; Rubio et al., 2005; Streatfield 2007). However, these affinity chromatography methods are often ineffective when purifying proteins from the complex plant proteome and are costly and difficult to scale up for industrial applications (Waugh, 2005).More recently, elastin-like polypeptide (ELP) and Zera protein fusions have been shown to significantly enhance recombinant protein accumulation in the leaves of plants (Patel et al., 2007; Floss et al., 2008; Conley et al., 2009c; Torrent et al., 2009) while also providing a means for their purification. ELPs are thermally responsive synthetic biopolymers composed of a repeating pentapeptide (VPGXG) sequence (Urry, 1988) that are valuable for the simple nonchromatographic “inverse transition cycling” bioseparation of recombinant proteins (Meyer and Chilkoti, 1999; Lin et al., 2006). However, the purity and recovery efficiency are rather low when using inverse transition cycling for the purification of plant-made proteins that accumulate to low levels, so expensive and tedious affinity chromatography steps are still needed in these cases (Conley et al., 2009a; Joensuu et al., 2009). Alternatively, Zera, the Pro-rich domain derived from the maize (Zea mays) seed storage protein γ-zein, can facilitate the recovery and purification of fused recombinant proteins by density-based separation methods, but this technique is difficult to scale up (Torrent et al., 2009). Interestingly, both of these protein fusions, derived from taxonomically distinct kingdoms, have been shown to induce the formation of novel endoplasmic reticulum (ER)-derived protein bodies (PBs; Conley et al., 2009b; Torrent et al., 2009). These PBs are physiologically inert and allow for the stable storage of large amounts of recombinant protein within the cell. To overcome the current limitations of the ELP and Zera purification schemes, we chose to investigate hydrophobins as fusion partners for the expression and purification of plant-made recombinant proteins, since they share many interesting physicochemical properties with ELP and Zera.Hydrophobins are small surface-active fungal proteins that have a characteristic pattern of eight conserved Cys residues, which form four intramolecular disulfide bridges and are responsible for stabilizing the protein''s structure (Hakanpaa et al., 2004). In nature, hydrophobins contribute to surface hydrophobicity and function to coat various fungal structures important for growth and development (Linder, 2009). Hydrophobins have a propensity to self-assemble into an amphipathic protein membrane at hydrophilic-hydrophobic interfaces (Wösten and de Vocht, 2000; Paananen et al., 2003; Wang et al., 2005). Because of these unique properties, hydrophobins have numerous potential applications, including the ability to interface proteins with nonbiological surfaces, to alter the wettability of different materials, to act as biosurfactants and oil stabilizers, and to form medical and technical coatings (Wessels, 1997; Askolin et al., 2001; Linder et al., 2005; Linder, 2009).Hydrophobins are also capable of altering the hydrophobicity of their respective fusion partners, thus enabling efficient purification using a surfactant-based aqueous two-phase system (ATPS; Linder et al., 2004). The ATPS concentrates the hydrophobin fusions inside micellar structures and partitions them toward the surfactant phase (Lahtinen et al., 2008). ATPSs offer several benefits, since they are simple, rapid, and inexpensive while providing volume reduction, high capacity, and fast separations (Persson et al., 1999). Most importantly, the one-step ATPS purification is particularly attractive because it can be easily and effectively scaled up for industrial-scale protein purification (Linder et al., 2004; Selber et al., 2004).Here, we used agroinfiltration to study the effect of a hydrophobin fusion on the accumulation of GFP and the commercially valuable enzyme Glc oxidase (GOx). We also determined the capability of hydrophobins for purifying recombinant proteins from leaf extracts using an ATPS. The hydrophobin fusion partner significantly enhanced the production yield of GFP while also providing a simple, efficient, and inexpensive approach for the purification of recombinant proteins from plants.