The phytohormone abscisic acid (ABA) mediates the adaptation of plants to environmental stresses such as drought and regulates developmental signals such as seed maturation. Within plants, the PYR/PYL/RCAR family of START proteins receives ABA to inhibit the phosphatase activity of the group-A protein phosphatases 2C (PP2Cs), which are major negative regulators in ABA signalling. Here we present the crystal structures of the ABA receptor PYL1 bound with (+)-ABA, and the complex formed by the further binding of (+)-ABA-bound PYL1 with the PP2C protein ABI1. PYL1 binds (+)-ABA using the START-protein-specific ligand-binding site, thereby forming a hydrophobic pocket on the surface of the closed lid. (+)-ABA-bound PYL1 tightly interacts with a PP2C domain of ABI1 by using the hydrophobic pocket to cover the active site of ABI1 like a plug. Our results reveal the structural basis of the mechanism of (+)-ABA-dependent inhibition of ABI1 by PYL1 in ABA signalling.

We report the complete genome sequence of Zymomonas mobilis ZM4 (ATCC31821), an ethanologenic microorganism of interest for the production of fuel ethanol. The genome consists of 2,056,416 base pairs forming a circular chromosome with 1,998 open reading frames (ORFs) and three ribosomal RNA transcription units. The genome lacks recognizable genes for 6-phosphofructokinase, an essential enzyme in the Embden-Meyerhof-Parnas pathway, and for two enzymes in the tricarboxylic acid cycle, the 2-oxoglutarate dehydrogenase complex and malate dehydrogenase, so glucose can be metabolized only by the Entner-Doudoroff pathway. Whole genome microarrays were used for genomic comparisons with the Z. mobilis type strain ZM1 (ATCC10988) revealing that 54 ORFs predicted to encode for transport and secretory proteins, transcriptional regulators and oxidoreductase in the ZM4 strain were absent from ZM1. Most of these ORFs were also found to be actively transcribed in association with ethanol production by ZM4.Growing environmental concerns over the use and depletion of nonrenewable energy resources, together with the recent price increases and instabilities in the international oil markets have stimulated an increasing interest in the use of fermentation processes for the large-scale production of alternative fuels such as ethanol. As such, ethanol-producing microorganisms, such as the Gram-negative bacterium Z. mobilis, have potential for the production of fuel ethanol.Z. mobilis, which is used in the tropics to produce pulque and alcoholic palm wines, uses the Entner-Doudoroff (ED) pathway to metabolize glucose, which results in only 1 mole of ATP being produced per mole of glucose 1 . The potential advantages of using Z. mobilis for ethanol production include: (i) its high and specific rates of sugar uptake and ethanol production, (ii) its production of ethanol at yields close to the theoretical maximum with relatively low biomass formation, (iii) its high ethanol tolerance of up to 16% (vol/vol) and (iv) its facility for genetic manipulation 2-6 . However, wild strains of Z. mobilis can use only glucose, fructose and sucrose as carbon substrates, so recent research has focused on the development of recombinant strains capable of using pentose sugars 7,8 for the conversion of cheaper lignocellulosic hydrolysates to ethanol. Improved mutants 9-11 as well as the application of metabolic flux analysis, sitedirected mutagenesis, specific gene deletion/insertion and metabolic engineering for strain developlment 12,13 have also been reported. A physical map of Z. mobilis ZM4 genome and the ribosomal transcriptional unit have been previously reported 14,15 . In the current paper, the features of the complete sequence of the Z. mobilis ZM4 genome are presented and genomic characters are compared with those of another Z. mobilis strain, ZM1.

Expression of genes encoding starch-degrading enzymes is regulated by glucose repression in the yeast Saccharomyces cerevisiae. We have identified a transcriptional repressor, Nrg1, in a genetic screen designed to reveal negative factors involved in the expression of STA1, which encodes a glucoamylase. The NRG1 gene encodes a 25-kDa C 2 H 2 zinc finger protein which specifically binds to two regions in the upstream activation sequence of the STA1 gene, as judged by gel retardation and DNase I footprinting analyses. Disruption of the NRG1 gene causes a fivefold increase in the level of the STA1 transcript in the presence of glucose. The expression of NRG1 itself is inhibited in the absence of glucose. DNA-bound LexA-Nrg1 represses transcription of a target gene 10.7-fold in a glucose-dependent manner, and this repression is abolished in both ssn6 and tup1 mutants. Two-hybrid and glutathione S-transferase pull-down experiments show an interaction of Nrg1 with Ssn6 both in vivo and in vitro. These findings indicate that Nrg1 acts as a DNA-binding repressor and mediates glucose repression of the STA1 gene expression by recruiting the Ssn6-Tup1 complex.In yeast, a large number of genes are turned off during growth on glucose (9, 37, 49). These glucose-repressible genes can be divided into three groups: (i) genes for metabolizing other carbon sources; (ii) genes encoding enzymes unique to gluconeogenesis; and (iii) genes involved in the Krebs cycle and in respiration. The Mig1 glucose repressor is a zinc finger protein and binds to the GC-rich motif identified in the promoters of several glucose-repressed genes, including the GAL1, GAL4, SUC2, and MAL genes (10,13,28,29). In the absence of glucose, the Snf1 kinase inhibits the function of Mig1 protein directly or indirectly, leading to derepression of glucose-repressed genes (3, 4). Nuclear translocation of Mig1 is regulated by differential phosphorylation of the protein in response to glucose availability, and recruitment of the general repression complex Ssn6-Tup1 to the DNA-bound Mig1 is required for the repression (5,17,48). Disruption of the MIG1 gene, however, only partially relieves glucose repression of SUC2 and has little or no effect on glucose repression of other genes whose promoters contain the Mig1-binding sites (27,31,37,50), indicating the involvement of other repressors in glucose repression. For instance, Mig2 was recently identified as a second repressor responsible for the remaining glucose repression of SUC2 and contains zinc fingers very similar to those of Mig1 (24).In Saccharomyces cerevisiae var. diastaticus, three unlinked homologous STA genes (STA1, STA2, and STA3) encode glucoamylase isozymes (GAI, GAII, and GAIII), which are responsible for enzymatic degradation of starch to glucose (16,22,25,32,35,47,52). Expression of the STA genes is regulated by complex interactions between positive and negative factors and their cognate elements (1,19,21,33,41). The negative regulation occurs at three different levels: (i) carbon catabolite repression...

A low pressure (2∼3 bar) nanoimprint lithography technique is developed that utilizes a thin fluoropolymer film (∼100 µm) mold. The flexible film mold allows imprinting of submicron pattern features at such a low pressure primarily due to "sequential" imprinting made possible by the mold flexibility and the conformal contact made between the film mold and the substrate. The surface energy of the fluoropolymer mold material is low enough that no mold surface treatment is needed for clean demolding. Easy replication of the film mold by a simple solvent casting is another advantage of the proposed method. Also the nanoscale (<100 nm) replication capability is demonstrated and discussed with a solvent-cast thin film fluoropolymer mold.

A new rice mutant Suweon 464 (S-464) derived from a high-quality rice, Ilpumbyeo (IP), revealed a striking difference in cooking quality from IP. The physicochemical properties of S-464 and IP were compared. S-464 was unusually high in amylose and fiber contents, had B-type crystallinity of starch, and had a markedly lower proportion of short chains in the distribution of glucan-chain fractions of debranched starch as compared with IP. Scanning electron microscopy revealed that starch granules of S-464 were much smaller in size than those of IP and that many of them were not separated from amyloplasts. The physicochemical properties of S-464 would contribute to poor gelatinization, lower swelling power, higher hardness, and less stickiness when cooked. Although S-464 may not be desirable for cooked rice, the mutant could be an excellent candidate for other processed food products on the basis of its unusual properties of starch and high fiber, protein, and lipid contents.

Korean red ginseng has shown therapeutic effects for a number of disease conditions. However, little is known about the antiinflammatory effect of Korean red ginseng saponin fraction (RGSF) in vitro and in vivo. Therefore, in this study, we showed that RGSF containing 20(S)-protopanaxadiol type saponins inhibited nitric oxide production and attenuated the release of tumor necrotic factor (TNF)-α, interleukin (IL)-6, granulocyte monocyte colony stimulating factor (GMCSF), and macrophage chemo-attractant protein-1 in lipopolysaccharide (LPS) stimulated murine macrophage RAW264.7 cells. Moreover, RGSF down-regulated the mRNA expressions of inducible nitric oxide synthase, cyclooxyginase-2, IL-1β, TNF-α, GMCSF, and IL-6. Furthermore, RGSF reduced the level of TNF-α in the serum and protected mice against LPS mediated endotoxic shock. In conclusion, these results indicated that ginsenosides from RGSF and their metabolites could be potential sources of therapeutic agents against inflammation.

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The accuracy of the vast amount of genotypic information generated by high-throughput genotyping technologies is crucial in haplotype analyses and linkage-disequilibrium mapping for complex diseases. To date, most automated programs lack quality measures for the allele calls; therefore, human interventions, which are both labor intensive and error prone, have to be performed. Here, we propose a novel genotype clustering algorithm, GeneScore, based on a bivariate t-mixture model, which assigns a set of probabilities for each data point belonging to the candidate genotype clusters. Furthermore, we describe an expectation-maximization (EM) algorithm for haplotype phasing, GenoSpectrum (GS)-EM, which can use probabilistic multilocus genotype matrices (called "GenoSpectrum") as inputs. Combining these two model-based algorithms, we can perform haplotype inference directly on raw readouts from a genotyping machine, such as the TaqMan assay. By using both simulated and real data sets, we demonstrate the advantages of our probabilistic approach over the current genotype scoring methods, in terms of both the accuracy of haplotype inference and the statistical power of haplotype-based association analyses.