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991.
BioMetals - A family of dioxidovanadium(V) complexes (1–4) of the type [Na(H2O)x]+[VVO2(HL1?4)]? (x?=?4, 4.5 and 7) where HL2? represents the dianionic form of...  相似文献   
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Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C4 metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C3 photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C4 photosynthesis to concentrate CO2 in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C4 photosynthesis is much more efficient than C3 photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C3 crop species to C4 metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C3 and C4 metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.  相似文献   
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The non-receptor tyrosine kinase c-Abl is activated in response to DNA damage and induces p73-dependent apoptosis. Here, we investigated c-Abl regulation of the homeodomain-interacting protein kinase 2 (HIPK2), an important regulator of p53-dependent apoptosis. c-Abl phosphorylated HIPK2 at several sites, and phosphorylation by c-Abl protected HIPK2 from degradation mediated by the ubiquitin E3 ligase Siah-1. c-Abl and HIPK2 synergized in activating p53 on apoptotic promoters in a reporter assay, and c-Abl was required for endogenous HIPK2 accumulation and phosphorylation of p53 at Ser46 in response to DNA damage by γ- and UV radiation. Accumulation of HIPK2 in nuclear speckles and association with promyelocytic leukemia protein (PML) in response to DNA damage were also dependent on c-Abl activity. At high cell density, the Hippo pathway inhibits DNA damage-induced c-Abl activation. Under this condition, DNA damage-induced HIPK2 accumulation, phosphorylation of p53 at Ser46, and apoptosis were attenuated. These data demonstrate a new mechanism for the induction of DNA damage-induced apoptosis by c-Abl and illustrate network interactions between serine/threonine and tyrosine kinases that dictate cell fate.  相似文献   
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Production of active TGF-β1 is one mechanism by which human regulatory T cells (Tregs) suppress immune responses. This production is regulated by glycoprotein A repetitions predominant (GARP), a transmembrane protein present on stimulated Tregs but not on other T lymphocytes (Th and CTLs). GARP forms disulfide bonds with proTGF-β1, favors its cleavage into latent inactive TGF-β1, induces the secretion and surface presentation of GARP·latent TGF-β1 complexes, and is required for activation of the cytokine in Tregs. We explored whether additional Treg-specific protein(s) associated with GARP·TGF-β1 complexes regulate TGF-β1 production in Tregs. We searched for such proteins by yeast two-hybrid assay, using GARP as a bait to screen a human Treg cDNA library. We identified lysosomal-associated transmembrane protein 4B (LAPTM4B), which interacts with GARP in mammalian cells and is expressed at higher levels in Tregs than in Th cells. LAPTM4B decreases cleavage of proTGF-β1, secretion of soluble latent TGF-β1, and surface presentation of GARP·TGF-β1 complexes by Tregs but does not contribute to TGF-β1 activation. Therefore, LAPTM4B binds to GARP and is a negative regulator of TGF-β1 production in human Tregs. It may play a role in the control of immune responses by decreasing Treg immunosuppression.  相似文献   
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