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.     

Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice

Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.Nearly one-third of the 54 million ha of the highly saline soils in the world are located in South and Southeast Asia. Rice (Oryza sativa), which is the primary source of calories and protein for these two regions, is very sensitive to salinity stress, with even moderate salinity levels known to decrease yields by 50% (Zeng et al., 2002). Projected sea level rise due to climate change is expected to increase saltwater ingress in coastal rice-growing regions of South and Southeast Asia. Therefore, development of salt-tolerant rice cultivars is essential to maintain rice productivity in the salinity-affected regions globally.Salt tolerance, defined as the ability to maintain growth and productivity in saline conditions, is a complex polygenic trait that may be influenced by distinct physiological mechanisms (Munns et al., 1982; Munns and Termaat, 1986; Cheeseman, 1988; Munns and Tester, 2008; Horie et al., 2012; for a comprehensive review of genes involved in salinity tolerance in rice, see Negrão et al., 2011) At the cellular level, plants respond to saline conditions in two phases, namely an osmotic (shoot ion independent) and an ionic stress phase, which can occur in an overlapping manner with varying intensity during the course of salinity stress (Munns and Termaat, 1986; Munns, 2002; Munns and James, 2003; Munns and Tester, 2008; Horie et al., 2012). During the osmotic stress phase, which occurs soon after the onset of salinity, the reduction in external osmotic potential disrupts water uptake and impedes cell expansion, which, at the whole plant level, leads to reduced growth rate (Matsuda and Riazi, 1981; Munns and Passioura, 1984; Rawson and Munns, 1984; Azaizeh and Steudle, 1991; Fricke and Peters, 2002; Fricke, 2004; Boursiac et al., 2005). As salinity stress persists over several days and weeks, sodium ions (Na⁺) accumulate to toxic levels, resulting in cell death and precocious leaf senescence (Lutts and Bouharmont, 1996; Munns, 2002; Munns and James, 2003; Ghanem et al., 2008). This is typically observed during the ionic phase of the salinity response (Munns, 2002; Munns and James, 2003; Munns and Tester, 2008). Plants possess distinct mechanisms to adapt to these osmotic and ionic stresses that are controlled by a suite of genes (Apse et al., 1999; Carvajal et al., 1999; Halfter et al., 2000; Ishitani et al., 2000; Shi et al., 2000; Zeng and Shannon, 2000; Rus et al., 2001; Berthomieu et al., 2003; Martínez-Ballesta et al., 2003; Boursiac et al., 2005, 2008; Ren et al., 2005; Huang et al., 2006; Davenport et al., 2007; Obata et al., 2007; Székely et al., 2008; Horie et al., 2011; Rivandi et al., 2011; Asano et al., 2012; Munns et al., 2012; Latz et al., 2013; Schmidt et al., 2013; Campo et al., 2014; Choi et al., 2014; Liu et al., 2014). The genetic basis of temporal adaptive responses to salinity stress remains to be explored in rice and other crops. This is primarily due to challenges in capturing the dynamic physiological responses to salinity for a large number of genotypes in a nondestructive manner. Manual phenotyping to detect incremental changes in growth rate during the osmotic stress and slight shifts in leaf color due to ionic stress is difficult to quantify for a large number of genotypes.In rice, at least one major quantitative trait loci (QTL; saltol) for salinity tolerance has been characterized based on end point measurements of biomass, senescence/injury, and Na⁺ and K⁺ concentrations (Bonilla et al., 2002; Lin et al., 2004; Thomson et al., 2010). SHOOT K⁺ CONTENT1 (SKC1) is the causative gene underlying the saltol region. SKC1 encodes a Na⁺-selective high-affinity potassium transporter that regulates Na⁺/K⁺ homeostasis during salinity stress (Ren et al., 2005). High levels of Na⁺ displace cellular K⁺, an essential element for several enzymatic reactions and physiological processes (Gierth and Mäser, 2007). The ability to maintain cellular K⁺ levels during salinity through the action of Na⁺-selective potassium transporters or Na⁺/H⁺ antiporters is a well-characterized tolerance mechanism in cereals including rice (Ren et al., 2005; Sunarpi et al., 2005; Huang et al., 2006; Møller et al., 2009; Mian et al., 2011; Munns et al., 2012).Numerous studies have utilized conventional linkage mapping to identify QTL for morphological and physiological responses to salinity in rice using discrete end point measurements (Bonilla et al., 2002; Lin et al., 2004; Ren et al., 2005; Negrão et al., 2011; Wang et al., 2012). However, the physiological adaptation to saline conditions is a complex continuous process that develops over time. While some accessions will exhibit similar end point phenotypic values, the genetic and physiological mechanisms giving rise to the similar phenotypes may be very different and the growth trajectories throughout the experiment may be distinct. Although single time point studies have yielded important information regarding the genetic basis of salinity tolerance, such approaches are too simple to reveal the genetic architecture of stress adaptation. With the advent of high-throughput image-based phenotyping platforms, it is now feasible to quantify dynamic responses during the stress treatment for a large number of genotypes (Berger et al., 2010; Golzarian et al., 2011; Chen et al., 2014; Honsdorf et al., 2014).Image-based phenotyping has been combined with genome-wide association studies (GWAS) and linkage mapping to examine the genetic basis of complex developmental processes (Busemeyer et al., 2013; Moore et al., 2013; Topp et al., 2013; Slovak et al., 2014; Würschum et al., 2014; Yang et al., 2014; Bac-Molenaar et al., 2015). Moreover, the introduction of the time axis provides a better understanding of the physiological processes underlying complex stress and developmental responses compared with single end point measurements (Zhang et al., 2012; Moore et al., 2013; Brown et al., 2014; Chen et al., 2014; Slovak et al., 2014; Bac-Molenaar et al., 2015). However, to date, no studies have implemented an association mapping approach using image-derived phenotypes to address the genetic basis of dynamic stress responses in plants. Image-based phenotyping offers several advantages over conventional phenotyping: (1) quantitative measurements can be recorded over discrete time points to capture morphological and physiological responses in a nondestructive manner, and (2) the use of various types of spectral imaging address phenotypes that are not detectable to the human eye such as chlorophyll fluorescence and leaf water content. Integrating dynamic phenotypic data and association mapping has the potential to query genetic diversity across hundreds of accessions for complex traits and provides much higher resolution compared with conventional linkage mapping. Here, we explored the dynamic growth and chlorophyll responses to salinity of a diverse set of rice accessions using high-throughput visible and fluorescence imaging. To assess the genetic basis of plant growth in saline conditions, a logistic model was used to describe the temporal growth responses and was incorporated into the statistical framework necessary for association mapping. Coupled with temporal fluorescence imaging, we present, to our knowledge, new insights into the genetic architecture of osmotic and ionic responses during salinity stress in rice.     

Surveying Rubisco Diversity and Temperature Response to Improve Crop Photosynthetic Efficiency

The threat to global food security of stagnating yields and population growth makes increasing crop productivity a critical goal over the coming decades. One key target for improving crop productivity and yields is increasing the efficiency of photosynthesis. Central to photosynthesis is Rubisco, which is a critical but often rate-limiting component. Here, we present full Rubisco catalytic properties measured at three temperatures for 75 plants species representing both crops and undomesticated plants from diverse climates. Some newly characterized Rubiscos were naturally “better” compared to crop enzymes and have the potential to improve crop photosynthetic efficiency. The temperature response of the various catalytic parameters was largely consistent across the diverse range of species, though absolute values showed significant variation in Rubisco catalysis, even between closely related species. An analysis of residue differences among the species characterized identified a number of candidate amino acid substitutions that will aid in advancing engineering of improved Rubisco in crop systems. This study provides new insights on the range of Rubisco catalysis and temperature response present in nature, and provides new information to include in models from leaf to canopy and ecosystem scale.In a changing climate and under pressure from a population set to hit nine billion by 2050, global food security will require massive changes to the way food is produced, distributed, and consumed (Ort et al., 2015). To match rising demand, agricultural production must increase by 50 to 70% in the next 35 years, and yet the gains in crop yields initiated by the green revolution are slowing, and in some cases, stagnating (Long and Ort, 2010; Ray et al., 2012). Among a number of areas being pursued to increase crop productivity and food production, improving photosynthetic efficiency is a clear target, offering great promise (Parry et al., 2007; von Caemmerer et al., 2012; Price et al., 2013; Ort et al., 2015). As the gatekeeper of carbon entry into the biosphere and often acting as the rate-limiting step of photosynthesis, Rubisco, the most abundant enzyme on the planet (Ellis, 1979), is an obvious and important target for improving crop photosynthetic efficiency.Rubisco is considered to exhibit comparatively poor catalysis, in terms of catalytic rate, specificity, and CO₂ affinity (Tcherkez et al., 2006; Andersson, 2008), leading to the suggestion that even small increases in catalytic efficiency may result in substantial improvements to carbon assimilation across a growing season (Zhu et al., 2004; Parry et al., 2013; Galmés et al., 2014a; Carmo-Silva et al., 2015). If combined with complimentary changes such as optimizing other components of the Calvin Benson or photorespiratory cycles (Raines, 2011; Peterhansel et al., 2013; Simkin et al., 2015), optimized canopy architecture (Drewry et al., 2014), or introducing elements of a carbon concentrating mechanism (Furbank et al., 2009; Lin et al., 2014a; Hanson et al., 2016; Long et al., 2016), Rubisco improvement presents an opportunity to dramatically increase the photosynthetic efficiency of crop plants (McGrath and Long, 2014; Long et al., 2015; Betti et al., 2016). A combination of the available strategies is essential for devising tailored solutions to meet the varied requirements of different crops and the diverse conditions under which they are typically grown around the world.Efforts to engineer an improved Rubisco have not yet produced a “super Rubisco” (Parry et al., 2007; Ort et al., 2015). However, advances in engineering precise changes in model systems continue to provide important developments that are increasing our understanding of Rubisco catalysis (Spreitzer et al., 2005; Whitney et al., 2011a, 2011b; Morita et al., 2014; Wilson et al., 2016), regulation (Andralojc et al., 2012; Carmo-Silva and Salvucci, 2013; Bracher et al., 2015), and biogenesis (Saschenbrecker et al., 2007; Whitney and Sharwood, 2008; Lin et al., 2014b; Hauser et al., 2015; Whitney et al., 2015).A complementary approach is to understand and exploit Rubisco natural diversity. Previous characterization of Rubisco from a limited number of species has not only demonstrated significant differences in the underlying catalytic parameters, but also suggests that further undiscovered diversity exists in nature and that the properties of some of these enzymes could be beneficial if present in crop plants (Carmo-Silva et al., 2015). Recent studies clearly illustrate the variation possible among even closely related species (Galmés et al., 2005, 2014b, 2014c; Kubien et al., 2008; Andralojc et al., 2014; Prins et al., 2016).Until recently, there have been relatively few attempts to characterize the consistency, or lack thereof, of temperature effects on in vitro Rubisco catalysis (Sharwood and Whitney, 2014), and often studies only consider a subset of Rubisco catalytic properties. This type of characterization is particularly important for future engineering efforts, enabling specific temperature effects to be factored into any attempts to modify crops for a future climate. In addition, the ability to coanalyze catalytic properties and DNA or amino acid sequence provides the opportunity to correlate sequence and biochemistry to inform engineering studies (Christin et al., 2008; Kapralov et al., 2011; Rosnow et al., 2015). While the amount of gene sequence information available grows rapidly with improving technology, knowledge of the corresponding biochemical variation resulting has yet to be determined (Cousins et al., 2010; Carmo-Silva et al., 2015; Sharwood and Whitney, 2014; Nunes-Nesi et al., 2016).This study aimed to characterize the catalytic properties of Rubisco from diverse species, comprising a broad range of monocots and dicots from diverse environments. The temperature dependence of Rubisco catalysis was evaluated to tailor Rubisco engineering for crop improvement in specific environments. Catalytic diversity was analyzed alongside the sequence of the Rubisco large subunit gene, rbcL, to identify potential catalytic switches for improving photosynthesis and productivity. In vitro results were compared to the average temperature of the warmest quarter in the regions where each species grows to investigate the role of temperature in modulating Rubisco catalysis.     

Phosphorylation of the C Terminus of RHD3 Has a Critical Role in Homotypic ER Membrane Fusion in Arabidopsis

The endoplasmic reticulum (ER) consists of dynamically changing tubules and cisternae. In animals and yeast, homotypic ER membrane fusion is mediated by fusogens (atlastin and Sey1p, respectively) that are membrane-associated dynamin-like GTPases. In Arabidopsis (Arabidopsis thaliana), another dynamin-like GTPase, ROOT HAIR DEFECTIVE3 (RHD3), has been proposed as an ER membrane fusogen, but direct evidence is lacking. Here, we show that RHD3 has an ER membrane fusion activity that is enhanced by phosphorylation of its C terminus. The ER network was RHD3-dependently reconstituted from the cytosol and microsome fraction of tobacco (Nicotiana tabacum) cultured cells by exogenously adding GTP, ATP, and F-actin. We next established an in vitro assay system of ER tubule formation with Arabidopsis ER vesicles, in which addition of GTP caused ER sac formation from the ER vesicles. Subsequent application of a shearing force to this system triggered the formation of tubules from the ER sacs in an RHD-dependent manner. Unexpectedly, in the absence of a shearing force, Ser/Thr kinase treatment triggered RHD3-dependent tubule formation. Mass spectrometry showed that RHD3 was phosphorylated at multiple Ser and Thr residues in the C terminus. An antibody against the RHD3 C-terminal peptide abolished kinase-triggered tubule formation. When the Ser cluster was deleted or when the Ser residues were replaced with Ala residues, kinase treatment had no effect on tubule formation. Kinase treatment induced the oligomerization of RHD3. Neither phosphorylation-dependent modulation of membrane fusion nor oligomerization has been reported for atlastin or Sey1p. Taken together, we propose that phosphorylation-stimulated oligomerization of RHD3 enhances ER membrane fusion to form the ER network.In eukaryotic cells, the endoplasmic reticulum (ER) is the organelle with the largest membrane area. The ER consists of an elaborate network of interconnected membrane tubules and cisternae that is continually moving and being remodeled (Friedman and Voeltz, 2011). In plant cells, ER movement and remodeling is primarily driven by the actin-myosin XI cytoskeleton (Sparkes et al., 2009; Ueda et al., 2010; Yokota et al., 2011; Griffing et al., 2014) and secondarily by the microtubule cytoskeleton (Hamada et al., 2014). Several factors involved in creating the ER architecture have been also identified (Anwar et al., 2012; Chen et al., 2012; Goyal and Blackstone, 2013; Sackmann, 2014; Stefano et al., 2014a; Westrate et al., 2015). Among them, ER membrane-bound GTPases, animal atlastins and yeast Sey1p (Synthetic Enhancement of Yop1), function as ER fusogens to form the interconnected tubular network (Hu et al., 2009; Orso et al., 2009; Anwar et al., 2012). Atlastin molecules on the two opposed membranes have been proposed to transiently dimerize to attract the two membranes to each other (Bian et al., 2011; Byrnes and Sondermann, 2011; Morin-Leisk et al., 2011; Moss et al., 2011; Lin et al., 2012; Byrnes et al., 2013). Closely attracted lipid bilayers are supposed to be destabilized by an amphipathic helical domain at the atlastin C terminus to facilitate membrane fusion (Bian et al., 2011; Liu et al., 2012; Faust et al., 2015). Knockdown of atlastins leads to fragmentation of the ER and unbranched ER tubules, while overexpression of atlastins enhances ER membrane fusion, which enlarges the ER profiles (Hu et al., 2009; Orso et al., 2009).An Arabidopsis (Arabidopsis thaliana) protein, ROOT HAIR DEFECTIVE3 (RHD3), has been proposed as a fusogen because (1) when it is disrupted, the ER network is modified into large cable-like strands of poorly branched membranes (Zheng et al., 2004; Chen et al., 2011; Stefano et al., 2012), (2) it shares sequence similarity with the above-mentioned fusogen Sey1p (Hu et al., 2009), and (3) it has structural similarity to atlastin and Sey1p, with a functional GTPase domain at the N-terminal cytosolic domain (Stefano et al., 2012) followed by two transmembrane domains and a cytosolic tail. RHD3 has a longer cytosolic C-terminal tail than do atlastin and Sey1p (Stefano and Brandizzi, 2014). It contains not only an amphipathic region but also a Ser/Thr-rich C terminus.Arabidopsis has two RHD3 isoforms called RHD3-Like 1 and RHD3-Like 2. Fluorescently tagged RHD3 and RHD3-Like 2 localize to the ER (Chen et al., 2011; Stefano et al., 2012; Lee et al., 2013). RHD3 and the two RHD3-Like proteins likely have redundant roles in ER membrane fusion (Zhang et al., 2013). Overexpression of either RHD3 or RHD3-Like 2 with a defective GTPase domain phenocopies the aberrant ER morphology in rhd3-deficient mutants (Chen et al., 2011; Lee et al., 2013).In this study, we show that the Ser/Thr-rich C terminus enhances ER membrane fusion following phosphorylation of its C terminus. We propose a model in which phosphorylation and oligomerization of RHD3 is required for efficient ER membrane fusion. Our findings clarify the mechanisms that regulate RHD3 and consequently the homeostasis of membrane fusion in the ER.     

Metabolite Profiles of Maize Leaves in Drought,Heat, and Combined Stress Field Trials Reveal the Relationship between Metabolism and Grain Yield

The development of abiotic stress-resistant cultivars is of premium importance for the agriculture of developing countries. Further progress in maize (Zea mays) performance under stresses is expected by combining marker-assisted breeding with metabolite markers. In order to dissect metabolic responses and to identify promising metabolite marker candidates, metabolite profiles of maize leaves were analyzed and compared with grain yield in field trials. Plants were grown under well-watered conditions (control) or exposed to drought, heat, and both stresses simultaneously. Trials were conducted in 2010 and 2011 using 10 tropical hybrids selected to exhibit diverse abiotic stress tolerance. Drought stress evoked the accumulation of many amino acids, including isoleucine, valine, threonine, and 4-aminobutanoate, which has been commonly reported in both field and greenhouse experiments in many plant species. Two photorespiratory amino acids, glycine and serine, and myoinositol also accumulated under drought. The combination of drought and heat evoked relatively few specific responses, and most of the metabolic changes were predictable from the sum of the responses to individual stresses. Statistical analysis revealed significant correlation between levels of glycine and myoinositol and grain yield under drought. Levels of myoinositol in control conditions were also related to grain yield under drought. Furthermore, multiple linear regression models very well explained the variation of grain yield via the combination of several metabolites. These results indicate the importance of photorespiration and raffinose family oligosaccharide metabolism in grain yield under drought and suggest single or multiple metabolites as potential metabolic markers for the breeding of abiotic stress-tolerant maize.The increasing world population coupled to environmental deterioration is creating ever greater pressure on our capacity for sustainable food productivity. Alongside biotic stresses, abiotic stresses such as drought, heat, salinity, and nutrient deficiency greatly reduce yields in crop fields either when present alone or in combination. Breeding for more resilient crops, therefore, is one of the major approaches to cope with the increasing challenges in world agriculture. Considerable research effort has thus been invested in order to dissect plant responses to individual stresses at various levels (for review, see Urano et al., 2010; Lopes et al., 2011; Obata and Fernie, 2012), but the interaction between different stresses has been far less investigated (Cairns et al., 2012b, 2013; Suzuki et al., 2014). In general, the combination of stresses additively affects plant physiology (i.e. the symptoms of the individual stresses appear simultaneously) and synergistically diminishes the yield and productivity of plants (Keleş and Öncel, 2002; Giraud et al., 2008; Vile et al., 2012; Suzuki et al., 2014). The molecular responses, however, are not simply additive and are rarely predicted from the responses to individual stresses (Rizhsky et al., 2002, 2004; Prasch and Sonnewald, 2013; Rasmussen et al., 2013). Information from carefully controlled greenhouse experiments has begun to dissect the molecular mechanisms by which plants, in particular Arabidopsis (Arabidopsis thaliana), respond to drought and temperature stresses (Skirycz et al., 2010, 2011; Skirycz and Inzé, 2010; Bowne et al., 2012; Tardieu, 2012; Verkest et al., 2015). Our knowledge of the molecular basis of the responses of crop species in a field environment, however, is considerably less well advanced (Araus et al., 2008; Cabrera-Bosquet et al., 2012). That said, a large number of genotypes have been generated on the basis of their resistance to both biotic and abiotic stresses (for review, see Bänziger et al., 2006; Takeda and Matsuoka, 2008; Cooper et al., 2014), and the genome sequencing and molecular characterization of a range of stress-tolerant plant species have recently been reported (Wu et al., 2012; Ma et al., 2013; Bolger et al., 2014; Tohge et al., 2014). These studies are not only important as basic research for further studies in crops but also are a prerequisite in the development of molecular marker-based approaches to improve crop tolerance to stress.As a first step toward this goal, a deeper understanding of the plant responses to the stressful environment, especially those to multiple stress conditions under field conditions, is crucial for the improvement of stress-tolerant crops. This is important on two levels: (1) in the field, singular abiotic stresses are rare; and (2) yield and stress adaptation are complex traits that render breeding gains slower than would be expected under optimal conditions (Bruce et al., 2002). Recent studies have revealed that the response of plants to combinations of two or more stress conditions is unique and cannot be directly extrapolated from their responses to the different stresses when applied individually. This would be a result of complex combinations of different, and sometimes opposing, responses in signaling pathways, including those that may interact and inhibit one another (Prasch and Sonnewald, 2013; Rasmussen et al., 2013; Suzuki et al., 2014).Maize (Zea mays) is grown in over 170 million ha worldwide, of which 130 million ha are in less-developed countries (FAO, 2014). In sub-Saharan Africa, maize is a staple crop; however, yields in this region have stagnated at less than 2 tons ha⁻¹, while maize yields worldwide have continued to increase (Cairns et al., 2012a). Low yields in sub-Saharan Africa are largely associated with drought stress (DS) and low soil fertility (Bänziger and Araus, 2007). Additionally, simulation studies indicate that maize yield in Africa is likely to be significantly impaired by heat stress (HS; Lobell and Burke, 2010; Lobell et al., 2011), such as can be anticipated as a result of the changes in climate predicted for the coming decades (Müller et al., 2011). Moreover, the sensitivity of maize yield to heat is exacerbated under drought conditions (Lobell et al., 2011; Cairns et al., 2012a, 2012b, 2013). Therefore, the development of maize germplasm tolerant to drought and heat conditions is of utmost importance to both increase yields and offset predicted yield losses under projected climate change scenarios (Easterling et al., 2007), especially in sub-Saharan Africa. While direct selection for grain yield under DS has resulted in admirable gains in grain yield under stress (Bänziger et al., 2006; Cairns et al., 2013), further improvement requires the incorporation of additional selection traits (Cairns et al., 2012a, 2012b). In recent years, genetic and phenotypic markers have been searched extensively for drought tolerance of maize by high-throughput genomic and phenotyping approaches, respectively (Tuberosa and Salvi, 2006; Wen et al., 2011; Araus et al., 2012; Cairns et al., 2013; Prasanna et al., 2013; Araus and Cairns, 2014; Tsonev et al., 2014). Moreover, metabolic markers started to draw attention due to their close relationship with yield phenotypes (Fernie and Schauer, 2009; Redestig et al., 2011; Riedelsheimer et al., 2012a, 2012b; Witt et al., 2012; Degenkolbe et al., 2013). The accumulation of some metabolites has been reported to be directly related to the performance of potato (Solanum tuberosum) cultivars in beetle resistance in the field (Tai et al., 2014). Additionally, identical genomic regions were mapped as both agronomic and metabolic quantitative trait loci in field-grown maize and wheat (Triticum aestivum), indicating the utility of metabolic traits for breeding selection (Riedelsheimer et al., 2012b; Hill et al., 2015). A recent study showed that genetic gains in maize grain yield under DS were higher using a molecular marker-based approach than conventional breeding (Beyene et al., 2015).Here, we focused on the relationship between leaf metabolites and grain yield under drought, heat, and simultaneous drought and heat conditions in the field. The negative effect of DS on maize yield is especially acute during the reproductive stage between tassel emergence and early grain filling (Grant et al., 1989), when it is believed to induce premature seed desiccation and to limit grain filling. Grain is more susceptible to DS than vegetative tissues; therefore, the prediction of grain yield from the physiological parameter of leaves is a challenge (Sangoi and Salvador, 1998; Khodarahmpour and Hamidi, 2011). Nevertheless, maize yield is dependent on both the assimilate supply to the kernel (source) and the potential of the kernel to accommodate this assimilate (sink potential; Jones and Simmons, 1983). Breeding for modern temperate hybrids has focused more on the sink potential, particularly under stress conditions (Tollenaar and Lee, 2006); therefore, there should be considerable potential remaining to improve source ability. DS and HS would be anticipated largely to affect leaf metabolism and especially photosynthesis, compromising the source capacity of leaves (Chaves et al., 2009; Lawlor and Tezara, 2009; Osakabe et al., 2014). In keeping with this, drought was found to have the most dramatic effect on the metabolite composition in leaves compared with other organs in our previous greenhouse experiments (Witt et al., 2012). Since the source ability is closely related to leaf metabolism, the leaf metabolite profile should have a close relationship to grain yield particularly under conditions of stress. Given that several recent studies have indicated the importance of metabolic preadaptation to various stress tolerances in plants (Sanchez et al., 2011; Benina et al., 2013), we also postulate that basal metabolite levels under optimal growth conditions could be correlated to stress tolerance. In order to test this, metabolite profiles of the leaf blades of 10 hybrids were analyzed in field experiments conducted at the International Maize and Wheat Improvement Center (CIMMYT) subtropical experimental station in 2010 and 2011 in which the plants were exposed to singular or combined drought and heat stresses (DS+HS; Cairns et al., 2012a, 2013). The results are discussed both in the context of current models of stress tolerance and with respect to their practical implications for future breeding strategies.     

Focus on Ethylene: Ethylene and the Regulation of Physiological and Morphological Responses to Nutrient Deficiencies

To cope with nutrient deficiencies, plants develop both morphological and physiological responses. The regulation of these responses is not totally understood, but some hormones and signaling substances have been implicated. It was suggested several years ago that ethylene participates in the regulation of responses to iron and phosphorous deficiency. More recently, its role has been extended to other deficiencies, such as potassium, sulfur, and others. The role of ethylene in so many deficiencies suggests that, to confer specificity to the different responses, it should act through different transduction pathways and/or in conjunction with other signals. In this update, the data supporting a role for ethylene in the regulation of responses to different nutrient deficiencies will be reviewed. In addition, the results suggesting the action of ethylene through different transduction pathways and its interaction with other hormones and signaling substances will be discussed.When plants suffer from a mineral nutrient deficiency, they develop morphological and physiological responses (mainly in their roots) aimed to facilitate the uptake and mobilization of the limiting nutrient. After the nutrient has been acquired in enough quantity, these responses need to be switched off to avoid toxicity and conserve energy. In recent years, different plant hormones (e.g. ethylene, auxin, cytokinins, jasmonic acid, abscisic acid, brassinosteroids, GAs, and strigolactones) have been implicated in the regulation of these responses (Romera et al., 2007, 2011, 2015; Liu et al., 2009; Rubio et al., 2009; Kapulnik et al., 2011; Kiba et al., 2011; Iqbal et al., 2013; Zhang et al., 2014).Before the 1990s, there were several publications relating ethylene and nutrient deficiencies (cited in Lynch and Brown [1997] and Romera et al. [1999]) without establishing a direct implication of ethylene in the regulation of nutrient deficiency responses. In 1994, Romera and Alcántara (1994) published an article in Plant Physiology suggesting a role for ethylene in the regulation of Fe deficiency responses. In 1999, Borch et al. (1999) showed the participation of ethylene in the regulation of P deficiency responses. Since then, evidence has been accumulating in support of a role for ethylene in the regulation of both Fe (Romera et al., 1999, 2015; Waters and Blevins, 2000; Lucena et al., 2006; Waters et al., 2007; García et al., 2010, 2011, 2013, 2014; Yang et al., 2014) and P deficiency responses (Kim et al., 2008; Lei et al., 2011; Li et al., 2011; Nagarajan and Smith, 2012; Wang et al., 2012, 2014c). Both Fe and P may be poorly available in most soils, and plants develop similar responses under their deficiencies (Romera and Alcántara, 2004; Zhang et al., 2014). More recently, a role for ethylene has been extended to other deficiencies, such as K (Shin and Schachtman, 2004; Jung et al., 2009; Kim et al., 2012), S (Maruyama-Nakashita et al., 2006; Wawrzyńska et al., 2010; Moniuszko et al., 2013), and B (Martín-Rejano et al., 2011). Ethylene has also been implicated in both N deficiency and excess (Tian et al., 2009; Mohd-Radzman et al., 2013; Zheng et al., 2013), and its participation in Mg deficiency has been suggested (Hermans et al., 2010).In this update, we will review the information supporting a role for ethylene in the regulation of different nutrient deficiency responses. For information relating ethylene to other aspects of plant mineral nutrition, such as N₂ fixation and responses to excess of nitrate or essential heavy metals, the reader is referred to other reviews (for review, see Maksymiec, 2007; Mohd-Radzman et al., 2013; Steffens, 2014).