Integrated functions among multiple starch synthases determine both amylopectin chain length and branch linkage location in Arabidopsis leaf starch

This study assessed the impact on starch metabolism in Arabidopsis leaves of simultaneously eliminating multiple soluble starch synthases (SS) from among SS1, SS2, and SS3. Double mutant ss1- ss2- or ss1- ss3- lines were generated using confirmed null mutations. These were compared to the wild type, each single mutant, and ss1- ss2- ss3- triple mutant lines grown in standardized environments. Double mutant plants developed similarly to the wild type, although they accumulated less leaf starch in both short-day and long-day diurnal cycles. Despite the reduced levels in the double mutants, lines containing only SS2 and SS4, or SS3 and SS4, are able to produce substantial amounts of starch granules. In both double mutants the residual starch was structurally modified including higher ratios of amylose:amylopectin, altered glucan chain length distribution within amylopectin, abnormal granule morphology, and altered placement of α(1→6) branch linkages relative to the reducing end of each linear chain. The data demonstrate that SS activity affects not only chain elongation but also the net result of branch placement accomplished by the balanced activities of starch branching enzymes and starch debranching enzymes. SS3 was shown partially to overlap in function with SS1 for the generation of short glucan chains within amylopectin. Compensatory functions that, in some instances, allow continued residual starch production in the absence of specific SS classes were identified, probaby accomplished by the granule bound starch synthase GBSS1.ANR Génoplante GPLA0611GEuropean Union-FEDER, Région Nord Pas de Calais ARCir PlantTEQ5National Science Foundation DBI-0209789Comisión Interministerial de Ciencia y Tecnología BIO2009-07040Junta de Andalucía P09-CVI-470

A Kiloparsec-Scale Binary Active Galactic Nucleus Confirmed by the Expanded Very Large Array

We report the confirmation of a kpc-scale binary active galactic nucleus (AGN) with high-resolution radio images from the Expanded Very Large Array (EVLA). SDSS J150243.1+111557 is a double-peaked [O III] AGN at z = 0.39 selected from the Sloan Digital Sky Survey. Our previous near-infrared adaptive optics imaging reveals two nuclei separated by 1.4" (7.4 kpc), and our optical integral-field spectroscopy suggests that they are a type-1--type-2 AGN pair. However, these data alone cannot rule out the single AGN scenario where the narrow emission-line region associated with the secondary is photoionized by the broad-line AGN in the primary. Our new EVLA images at 1.4, 5.0, and 8.5 GHz show two steep-spectrum compact radio sources spatially coincident with the optical nuclei. The radio power of the type-2 AGN is an order-of-magnitude in excess of star-forming galaxies with similar extinction-corrected [O II] 3727 luminosities, indicating that the radio emission is powered by accretion. Therefore, SDSS J150243.1+111557 is one of the few confirmed kpc-scale binary AGN systems. Spectral-energy-distribution modeling shows that SDSS J150243.1+111557 is a merger of two ~10^{11} M_sun galaxies. With both black hole masses around 10^8 Msun, the AGNs are accreting at ~10 times below the Eddington limit.Comment: ApJL accepted. 6 pages, 3 figures, 1 tabl

Proteome and phosphoproteome analysis of starch granule-associated proteins from normal maize and mutants affected in starch biosynthesis

In addition to the exclusively granule-bound starch synthase GBSSI, starch granules also bind significant proportions of other starch biosynthetic enzymes, particularly starch synthases (SS) SSI and SSIIa, and starch branching enzyme (BE) BEIIb. Whether this association is a functional aspect of starch biosynthesis, or results from non-specific entrapment during amylopectin crystallization, is not known. This study utilized genetic, immunological, and proteomic approaches to investigate comprehensively the proteome and phosphoproteome of Zea mays endosperm starch granules. SSIII, BEI, BEIIa, and starch phosphorylase were identified as internal granule-associated proteins in maize endosperm, along with the previously identified proteins GBSS, SSI, SSIIa, and BEIIb. Genetic analyses revealed three instances in which granule association of one protein is affected by the absence of another biosynthetic enzyme. First, eliminating SSIIa caused reduced granule association of SSI and BEIIb, without affecting GBSS abundance. Second, eliminating SSIII caused the appearance of two distinct electrophoretic mobility forms of BEIIb, whereas only a single migration form of BEIIb was observed in wild type or any other mutant granules examined. Third, eliminating BEIIb caused significant increases in the abundance of BEI, BEIIa, SSIII, and starch phosphorylase in the granule, without affecting SSI or SSIIa. Analysis of the granule phosphoproteome with a phosphorylation-specific dye indicated that GBSS, BEIIb, and starch phosphorylase are all phosphorylated as they occur in the granule. These results suggest the possibility that starch metabolic enzymes located in granules are regulated by post-translational modification and/or protein–protein interactions

Mean Field Theory of Collective Transport with Phase Slips

The driven transport of plastic systems in various disordered backgrounds is studied within mean field theory. Plasticity is modeled using non-convex interparticle potentials that allow for phase slips. This theory most naturally describes sliding charge density waves; other applications include flow of colloidal particles or driven magnetic flux vortices in disordered backgrounds. The phase diagrams exhibit generic phases and phase boundaries, though the shapes of the phase boundaries depend on the shape of the disorder potential. The phases are distinguished by their velocity and coherence: the moving phase generically has finite coherence, while pinned states can be coherent or incoherent. The coherent and incoherent static phases can coexist in parameter space, in contrast with previous results for exactly sinusoidal pinning potentials. Transitions between the moving and static states can also be hysteretic. The depinning transition from the static to sliding states can be determined analytically, while the repinning transition from the moving to the pinned phases is computed by direct simulation.Comment: 30 pages, 29 figure

Overlapping functions of the starch synthases SSII and SSIII in amylopectin biosynthesis in Arabidopsis

Background: The biochemical mechanisms that determine the molecular architecture of amylopectin are central in plant biology because they allow long-term storage of reduced carbon. Amylopectin structure imparts the ability to form semi-crystalline starch granules, which in turn provides its glucose storage function. The enzymatic steps of amylopectin biosynthesis resemble those of the soluble polymer glycogen, however, the reasons for amylopectin's architectural distinctions are not clearly understood. The multiplicity of starch biosynthetic enzymes conserved in plants likely is involved. For example, amylopectin chain elongation in plants involves five conserved classes of starch synthase (SS), whereas glycogen biosynthesis typically requires only one class of glycogen synthase. Results: Null mutations were characterized in AtSS2, which codes for SSII, and mutant lines were compared to lines lacking SSIII and to an Atss2, Atss3 double mutant. Loss of SSII did not affect growth rate or starch quantity, but caused increased amylose/amylopectin ratio, increased total amylose, and deficiency in amylopectin chains with degree of polymerization (DP) 12 to DP28. In contrast, loss of both SSII and SSIII caused slower plant growth and dramatically reduced starch content. Extreme deficiency in DP12 to DP28 chains occurred in the double mutant, far more severe than the summed changes in SSII- or SSIII-deficient plants lacking only one of the two enzymes. Conclusion: SSII and SSIII have partially redundant functions in determination of amylopectin structure, and these roles cannot be substituted by any other conserved SS, specifically SSI, GBSSI, or SSIV. Even though SSIII is not required for the normal abundance of glucan chains of DP12 to DP18, the enzyme clearly is capable of functioning in production such chains. The role of SSIII in producing these chains cannot be detected simply by analysis of an individual mutation. Competition between different SSs for binding to substrate could in part explain the specific distribution of glucan chains within amylopectin

Thermal error modelling of machine tools based on ANFIS with fuzzy c-means clustering using a thermal imaging camera

Thermal errors are often quoted as being the largest contributor to CNC machine tool errors, but they can be effectively reduced using error compensation. The performance of a thermal error compensation system depends on the accuracy and robustness of the thermal error model and the quality of the inputs to the model. The location of temperature measurement must provide a representative measurement of the change in temperature that will affect the machine structure. The number of sensors and their locations are not always intuitive and the time required to identify the optimal locations is often prohibitive, resulting in compromise and poor results. In this paper, a new intelligent compensation system for reducing thermal errors of machine tools using data obtained from a thermal imaging camera is introduced. Different groups of key temperature points were identified from thermal images using a novel schema based on a Grey model GM (0, N) and Fuzzy c-means (FCM) clustering method. An Adaptive Neuro-Fuzzy Inference System with Fuzzy c-means clustering (FCM-ANFIS) was employed to design the thermal prediction model. In order to optimise the approach, a parametric study was carried out by changing the number of inputs and number of membership functions to the FCM-ANFIS model, and comparing the relative robustness of the designs. According to the results, the FCM-ANFIS model with four inputs and six membership functions achieves the best performance in terms of the accuracy of its predictive ability. The residual value of the model is smaller than ± 2 μm, which represents a 95% reduction in the thermally-induced error on the machine. Finally, the proposed method is shown to compare favourably against an Artificial Neural Network (ANN) model

A Vehicle for Research: Using Street Sweepers to Explore the Landscape of Environmental Community Action

Researchers are developing mobile sensing platforms to facilitate public awareness of environmental conditions. However, turning such awareness into practical community action and political change requires more than just collecting and presenting data. To inform research on mobile environmental sensing, we conducted design fieldwork with government, private, and public interest stakeholders. In parallel, we built an environmental air quality sensing system and deployed it on street sweeping vehicles in a major U.S. city; this served as a "research vehicle" by grounding our interviews and affording us status as environmental action researchers. In this paper, we present a qualitative analysis of the landscape of environmental action, focusing on insights that will help researchers frame meaningful technological interventions.Comment: 10 page