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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.  相似文献   

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Transgenic tomato (Solanum lycopersicum) plants in which either mitochondrial malate dehydrogenase or fumarase was antisense inhibited have previously been characterized to exhibit altered photosynthetic metabolism. Here, we demonstrate that these manipulations also resulted in differences in root growth, with both transgenics being characterized by a dramatic reduction of root dry matter deposition and respiratory activity but opposite changes with respect to root area. A range of physiological, molecular, and biochemical experiments were carried out in order to determine whether changes in root morphology were due to altered metabolism within the root itself, alterations in the nature of the transformants'' root exudation, consequences of alteration in the efficiency of photoassimilate delivery to the root, or a combination of these factors. Grafting experiments in which the transformants were reciprocally grafted to wild-type controls suggested that root length and area were determined by the aerial part of the plant but that biomass was not. Despite the transgenic roots displaying alteration in the expression of phytohormone-associated genes, evaluation of the levels of the hormones themselves revealed that, with the exception of gibberellins, they were largely unaltered. When taken together, these combined experiments suggest that root biomass and growth are retarded by root-specific alterations in metabolism and gibberellin contents. These data are discussed in the context of current models of root growth and biomass partitioning.The structure of the plant tricarboxylic acid (TCA) cycle has been established for decades (Beevers, 1961), and in vitro studies have established regulatory properties of many of its component enzymes (Budde and Randall, 1990; Millar and Leaver, 2000; Studart-Guimarães et al., 2005). That said, relatively little is known, as yet, regarding how this important pathway is regulated in vivo (Fernie et al., 2004a; Sweetlove et al., 2007). Indeed, even fundamental questions concerning the degree to which this pathway operates in illuminated leaves (Tcherkez et al., 2005; Nunes-Nesi et al., 2007a) and the influence it has on organic acid levels in fruits (Burger et al., 2003) remain contentious. Furthermore, in contrast to many other pathways of primary metabolism, the TCA cycle has been subjected to relatively few molecular physiological studies. To date, the functions of pyruvate dehydrogenase, citrate synthase, aconitase, isocitrate dehydrogenase, succinyl-CoA ligase, fumarase, and malate dehydrogenase have been studied via this approach (Landschütze et al., 1995; Carrari et al., 2003; Yui et al., 2003; Nunes-Nesi et al., 2005, 2007a; Lemaitre et al., 2007; Studart-Guimarães et al., 2007); however, several of these studies were relatively cursory. Despite this fact, they generally corroborate one another, with at least two studies providing clear evidence for an important role of the TCA cycle in flower development (Landschütze et al., 1995; Yui et al., 2003) or in the coordination of photosynthetic and respiratory metabolisms of the illuminated leaf (Carrari et al., 2003; Nunes-Nesi et al., 2005, 2007a).In our own studies on tomato (Solanum lycopersicum), we have observed that modulation of fumarase and mitochondrial malate dehydrogenase activities leads to contrasting shoot phenotypes, with the former displaying stunted growth while the later exhibited an enhanced photosynthetic performance (Nunes-Nesi et al., 2005, 2007a). We were able to demonstrate that the stunted-growth phenotype observed in aerial parts of the fumarase plants was a consequence of altered stomatal function (Nunes-Nesi et al., 2007a), whereas the increased photosynthetic performance of the mitochondrial malate dehydrogenase seems likely to be mediated by the alterations in ascorbate metabolism exhibited by these plants (Nunes-Nesi et al., 2005; Urbanczyk-Wochniak et al., 2006). In keeping with the altered rates of photosynthesis in these antisense plants, the fruit yield of fumarase and mitochondrial malate dehydrogenase plants was decreased and increased, respectively. However, the root biomass of both transgenics was significantly reduced (Nunes-Nesi et al., 2005, 2007a). These observations were somewhat surprising given that it is estimated that 30% to 60% of net photosynthate is transported to root organs (Merckx et al., 1986; Nguyen et al., 1999; Singer et al., 2003). When taken together, these results suggest that the root phenotype must result from either an impairment of translocation or a root-specific effect. Neither of these explanations is without precedence, with inhibition of the expression of Suc transporters (Riesmeier et al., 1993; Gottwald et al., 2000) resulting in dramatically impaired root growth while organic acid exudation itself has been implicated in a wide range of root organ functions, including nutrient acquisition (de la Fuente et al., 1997; Imas et al., 1997; Neumann and Römheld, 1999; López-Bucio et al., 2000; Anoop et al., 2003; Delhaize et al., 2004), metal sequestration (Gillooly et al., 1983; de la Fuente et al., 1997; Cramer and Titus, 2001), and microbial proliferation in the rhizosphere (Lugtenberg et al., 1999; Weisskopf et al., 2005). In addition to the putative mechanisms listed above, the TCA cycle could be anticipated to play a vital role in meeting the high energy demands of nitrogen fixation and polymer biosynthesis associated with rapidly growing heterotrophic organs (Pradet and Raymond, 1983; Dieuaide-Noubhani et al., 1997; Stasolla et al., 2003; Deuschle et al., 2006). In keeping with this theory, alteration of the energy status of roots and other heterotrophic tissue has been documented to positively correlate with elevated biomass production (Anekonda, 2001; Regierer et al., 2002; Carrari et al., 2003; Lovas et al., 2003; Geigenberger et al., 2005). Here, we performed a detailed physiological, molecular, and biochemical evaluation of whole plant and root metabolism of the mitochondrial malate dehydrogenase and fumarate antisense tomato lines. In this manner, we broadly assessed biochemical changes in the root, including the levels of several major phytohormones, as well as dissected which characteristics were influenced by aerial parts of the plant. The results obtained are discussed both with respect to the regulation of the TCA cycle per se and within the context of the determination of root morphology and growth.  相似文献   

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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.  相似文献   

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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.  相似文献   

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The mitochondrial inner membrane contains a large protein complex that functions in inner membrane organization and formation of membrane contact sites. The complex was variably named the mitochondrial contact site complex, mitochondrial inner membrane organizing system, mitochondrial organizing structure, or Mitofilin/Fcj1 complex. To facilitate future studies, we propose to unify the nomenclature and term the complex “mitochondrial contact site and cristae organizing system” and its subunits Mic10 to Mic60.Mitochondria possess two membranes of different architecture and function (Palade, 1952; Hackenbrock, 1968). Both membranes work together for essential shared functions, such as protein import (Schatz, 1996; Neupert and Herrmann, 2007; Chacinska et al., 2009). The outer membrane harbors machinery that controls the shape of the organelle and is crucial for the communication of mitochondria with the rest of the cell. The inner membrane harbors the complexes of the respiratory chain, the F1Fo-ATP synthase, numerous metabolite carriers, and enzymes of mitochondrial metabolism. It consists of two domains: the inner boundary membrane, which is adjacent to the outer membrane, and invaginations of different shape, termed cristae (Werner and Neupert, 1972; Frey and Mannella, 2000; Hoppins et al., 2007; Pellegrini and Scorrano, 2007; Zick et al., 2009; Davies et al., 2011). Tubular openings, termed crista junctions (Perkins et al., 1997), connect inner boundary membrane and cristae membranes (Fig. 1, A and B). Respiratory chain complexes and the F1Fo-ATP synthase are preferentially located in the cristae membranes, whereas preprotein translocases are enriched in the inner boundary membrane (Vogel et al., 2006; Wurm and Jakobs, 2006; Davies et al., 2011). Contact sites between outer membrane and inner boundary membrane promote import of preproteins, metabolite channeling, lipid transport, and membrane dynamics (Frey and Mannella, 2000; Sesaki and Jensen, 2004; Hoppins et al., 2007, 2011; Neupert and Herrmann, 2007; Chacinska et al., 2009; Connerth et al., 2012; van der Laan et al., 2012).Open in a separate windowFigure 1.MICOS complex. (A) The MICOS complex (hypothetical model), previously also termed MINOS, MitOS, or Mitofilin/Fcj1 complex, is required for maintenance of the characteristic architecture of the mitochondrial inner membrane (IM) and forms contact sites with the outer membrane (OM). In budding yeast, six subunits of MICOS have been identified. All subunits are exposed to the intermembrane space (IMS), five are integral inner membrane proteins (Mic10, Mic12, Mic26, Mic27, and Mic60), and one is a peripheral inner membrane protein (Mic19). Mic26 is related to Mic27; however, mic26Δ yeast cells show considerably less severe defects of mitochondrial inner membrane architecture than mic27Δ cells (Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011). The MICOS complex of metazoa additionally contains Mic25, which is related to Mic19, yet subunits corresponding to Mic12 and Mic26 have not been identified so far. MICOS subunits that have been conserved in most organisms analyzed are indicated by bold boundary lines. (B, top) Wild-type architecture of the mitochondrial inner membrane with crista junctions and cristae. (bottom) This architecture is considerably altered in micos mutant mitochondria: most cristae membranes are detached from the inner boundary membrane and form internal membrane stacks. In some micos mutants (deficiency of mammalian Mic19 or Mic25), a loss of cristae membranes was observed (Darshi et al., 2011; An et al., 2012). Figure by M. Bohnert (Institute of Biochemistry and Molecular Biology, University of Freiburg, Freiburg, Germany).To understand the complex architecture of mitochondria, it will be crucial to identify the molecular machineries that control the interaction between mitochondrial outer and inner membranes and the characteristic organization of the inner membrane. A convergence of independent studies led to the identification of a large heterooligomeric protein complex of the mitochondrial inner membrane conserved from yeast to humans that plays crucial roles in the maintenance of crista junctions, inner membrane architecture, and formation of contact sites to the outer membrane (Fig. 1 A). Several names were used by different research groups to describe the complex, including mitochondrial contact site (MICOS) complex, mitochondrial inner membrane organizing system (MINOS), mitochondrial organizing structure (MitOS), Mitofilin complex, or Fcj1 (formation of crista junction protein 1) complex (Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012). Mitofilin, also termed Fcj1, was the first component identified (Icho et al., 1994; Odgren et al., 1996; Gieffers et al., 1997; John et al., 2005) and was observed enriched at crista junctions (Rabl et al., 2009). Mutants of Mitofilin/Fcj1 as well as of other MICOS/MINOS/MitOS subunits show a strikingly altered inner membrane architecture. They lose crista junctions and contain large internal membrane stacks, the respiratory activity is reduced, and mitochondrial DNA nucleoids are altered (Fig. 1 B; John et al., 2005; Hess et al., 2009; Rabl et al., 2009; Mun et al., 2010; Harner et al., 2011; Head et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; Itoh et al., 2013). It has been reported that the complex interacts with a variety of outer membrane proteins, such as channel proteins and components of the protein translocases and mitochondrial fusion machines, and defects impair the biogenesis of mitochondrial proteins (Xie et al., 2007; Darshi et al., 2011; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; An et al., 2012; Bohnert et al., 2012; Körner et al., 2012; Ott et al., 2012; Zerbes et al., 2012; Jans et al., 2013; Weber et al., 2013). The MICOS/MINOS/MitOS/Mitofilin/Fcj1 complex thus plays crucial roles in mitochondrial architecture, dynamics, and biogenesis. However, communication of results in this rapidly developing field has been complicated by several different nomenclatures used for the complex as well as for its subunits (
Standard nameFormer namesYeast ORFReferences
Complex
MICOSMINOS, MitOS, MIB, Mitofilin complex, and Fcj1 complexXie et al., 2007; Rabl et al., 2009; Darshi et al., 2011; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; An et al., 2012; Bohnert et al., 2012; Ott et al., 2012; Jans et al., 2013; Weber et al., 2013
Subunits
Mic10Mcs10, Mio10, Mos1, and MINOS1YCL057C-AHarner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Alkhaja et al., 2012; Itoh et al., 2013; Jans et al., 2013; Varabyova et al., 2013
Mic12Aim5, Fmp51, and Mcs12YBR262CHess et al., 2009; Harner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Varabyova et al., 2013
Mic19Aim13, Mcs19, CHCH-3, CHCHD3, and MINOS3YFR011CXie et al., 2007; Hess et al., 2009; Darshi et al., 2011; Head et al., 2011; Alkhaja et al., 2012; Ott et al., 2012; Jans et al., 2013; Varabyova et al., 2013
Mic25 (metazoan Mic19 homologue)CHCHD6 and CHCM1Xie et al., 2007; An et al., 2012
Mic26Mcs29, Mio27, and Mos2YGR235CHarner et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011
Mic27Aim37, Mcs27, APOOL, and MOMA-1YNL100WHess et al., 2009; Harner et al., 2011; Head et al., 2011; Hoppins et al., 2011; von der Malsburg et al., 2011; Weber et al., 2013
Mic60Fcj1, Aim28, Fmp13, Mitofilin, HMP, IMMT, and MINOS2YKR016WIcho et al., 1994; Odgren et al., 1996; Gieffers et al., 1997; John et al., 2005; Wang et al., 2008; Rabl et al., 2009; Rossi et al., 2009; Mun et al., 2010; Park et al., 2010; Körner et al., 2012; Zerbes et al., 2012; Itoh et al., 2013; Varabyova et al., 2013
Open in a separate windowAPOOL, apolipoprotein O–like; HMP, heart muscle protein; IMMT, inner mitochondrial membrane protein; MIB, mitochondrial intermembrane space bridging.To rectify this situation, all authors of this article have agreed on a new uniform nomenclature with the following guidelines. (a) The complex will be called “mitochondrial contact site and cristae organizing system” (MICOS). The protein subunits of MICOS are named Mic10 to Mic60 as listed in Gabriel et al., 2007; Vögtle et al., 2012) will be changed to Mix14, Mix17, and Mix23 (mitochondrial intermembrane space CXnC motif proteins) in the Saccharomyces Genome Database, and the new nomenclature will be used for orthologues identified in other organisms.The MICOS complex is of central importance for the maintenance of mitochondrial inner membrane architecture and the formation of contact sites between outer and inner membranes and thus is involved in the regulation of mitochondrial dynamics, biogenesis, and inheritance. We expect that the uniform nomenclature will facilitate future studies on mitochondrial membrane architecture and dynamics.  相似文献   

17.
The Interplay between Carbon Availability and Growth in Different Zones of the Growing Maize Leaf   总被引:1,自引:0,他引:1  
Angelika Czedik-Eysenberg  Stéphanie Arrivault  Marc A. Lohse  Regina Feil  Nicole Krohn  Beatrice Encke  Adriano Nunes-Nesi  Alisdair R. Fernie  John E. Lunn  Ronan Sulpice  Mark Stitt 《Plant physiology》2016,172(2):943-967
  相似文献   

18.
CYTOKININ OXIDASE/DEHYDROGENASE3 Maintains Cytokinin Homeostasis during Root and Nodule Development in Lotus japonicus     
Dugald E. Reid  Anne B. Heckmann  Ond?ej Novák  Simon Kelly  Jens Stougaard 《Plant physiology》2016,170(2):1060-1074
  相似文献   

19.
SUCROSE NONFERMENTING1-RELATED PROTEIN KINASE2.6, an Ortholog of OPEN STOMATA1, Is a Negative Regulator of Strawberry Fruit Development and Ripening     
Yu Han  Ruihong Dang  Jinxi Li  Jinzhu Jiang  Ning Zhang  Meiru Jia  Lingzhi Wei  Ziqiang Li  Bingbing Li  Wensuo Jia 《Plant physiology》2015,167(3):915-930
  相似文献   

20.
Surveying Rubisco Diversity and Temperature Response to Improve Crop Photosynthetic Efficiency     
Douglas J. Orr  André Alcantara  Maxim V. Kapralov  P. John Andralojc  Elizabete Carmo-Silva  Martin A.J. Parry 《Plant physiology》2016,172(2):707-717
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.  相似文献   

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