1,226 research outputs found
Datasets for transcriptomics, q-proteomics and phenotype microarrays of polyphosphate metabolism mutants from Escherichia coli
Indexación: Scopus.Author acknowledges Fondecyt Grants 1120209, 1121170 and Anillo ACT-1107Here, we provide the dataset associated with our research article on the polyphosphate metabolism entitled, “Multi-level evaluation of Escherichia coli polyphosphate related mutants using global transcriptomic, proteomic and phenomic analyses”. By integrating different omics levels (transcriptome, proteome and phenome), we were able to study Escherichia coli polyphosphate mutant strains (Δppk1, Δppx, and Δppk1-ppx). We have compiled here all datasets from DNA microarrys, q-proteomic (Isotope-Coded Protein Labeling, ICPL) and phenomic (Phenotype microarray) raw data we have obtained in all polyP metabolism mutants.http://www.sciencedirect.com/science/article/pii/S2352340917300860?via%3Dihu
Determinants of Alanine Dipeptide Conformational Equilibria on Graphene and Hydroxylated Derivatives
Citation: Poblete, H., Miranda-Carvajal, I., & Comer, J. (2017). Determinants of Alanine Dipeptide Conformational Equilibria on Graphene and Hydroxylated Derivatives. The Journal of Physical Chemistry B. https://doi.org/10.1021/acs.jpcb.7b01130Understanding the interaction of carbon nanomaterials with proteins is essential for determining the potential effects of these materials on health and in the design of biotechnology based on them. Here we leverage explicit-solvent molecular simulation and multidimensional free-energy calculations to investigate how adsorption to carbon nanomaterial surfaces affects the conformational equilibrium of alanine dipeptide, a widely used model of protein backbone structure. We find that the two most favorable structures of alanine dipeptide on graphene (or large carbon nanotubes) correspond to the two amide linkages lying in the same plane, flat against the surface, rather than the nonplanar ?-helix-like and ?-sheet-like conformations that predominate in aqueous solution. On graphenic surfaces, the latter conformations are metastable and most often correspond to amide?? stacking of the N-terminal amide. The calculations highlight the key role of amide?? interactions in determining the conformational equilibrium. Lesser but significant contributions from hydrogen bonding to the high density interfacial water layer or to the hydroxy groups of hydroxylated graphene also define the most favorable conformations. This work should yield insight on the influence of carbon nanotubes, graphene, and their functionalized derivatives on protein structure
Voltage-sensor transitions of the inward-rectifying K+ channel KAT1 indicate a latching mechanism biased by hydration within the voltage sensor
The Kv-like K+ channels at the plasma membrane, including the inward-rectifying KAT1 K+ channel of Arabidopsis, are important targets for manipulating K+ homeostasis in plants. Gating modification, especially, has been identified as a promising means by which to engineer plants with improved characteristics in mineral and water use. Understanding plant K+ channel gating poses several challenges, despite many similarities to that of mammalian Kv and Shaker channel models. We have used site-mutagenesis to explore residues that are thought to form two electrostatic counter-charge centers either side of a conserved Phe residue within the S2 and S3 α-helices of the voltage sensor domain (VSD) of Kv channels. Consistent with molecular dynamic simulations of KAT1, we show that the voltage dependence of the channel gate is highly sensitive to manipulations affecting these residues. Mutations of the central Phe residue favored the closed KAT1 channel, whereas mutations affecting the counter-charge centers favored the open channel. Modelling of the macroscopic current kinetics also highlighted a substantial difference between the two sets of mutations. We interpret these findings in context of the effects on hydration of amino-acid residues within the VSD and with an inherent bias of the VSD, when hydrated around a central Phe residue, to the closed state of the channel
Predicting Adsorption Affinities of Small Molecules on Carbon Nanotubes Using Molecular Dynamics Simulation
Citation: Comer, J., Chen, R., Poblete, H., Vergara-Jaque, A., & Riviere, J. E. (2015). Predicting Adsorption Affinities of Small Molecules on Carbon Nanotubes Using Molecular Dynamics Simulation. ACS Nano, 9(12), 11761–11774. https://doi.org/10.1021/acsnano.5b03592Computational techniques have the potential to accelerate the design and optimization of nanomaterials for applications such as drug delivery and contaminant removal; however, the success of such techniques requires reliable models of nanomaterial surfaces as well as accurate descriptions of their interactions with relevant solutes. In the present work, we evaluate the ability of selected models of naked and hydroxylated carbon nanotubes to predict adsorption equilibrium constants for about 30 small aromatic compounds with a variety of functional groups. The equilibrium constants determined using molecular dynamics coupled with free-energy calculation techniques are directly compared to those derived from experimental measurements. The calculations are highly predictive of the relative adsorption affinities of the compounds, with excellent correlation (r ? 0.9) between calculated and measured values of the logarithm of the adsorption equilibrium constant. Moreover, the agreement in absolute terms is also reasonable, with average errors of less than one decade. We also explore possible effects of surface loading, although we demonstrate that they are negligible for the experimental conditions considered. Given the degree of reliability demonstrated, we move on to employing the in silico techniques in the design of nanomaterials, using the optimization of adsorption affinity for the herbacide atrazine as an example. Our simulations suggest that, compared to other modifications of graphenic carbon, polyvinylpyrrolidone conjugation gives the highest affinity for atrazine—substantially greater than that of graphenic carbon alone—and may be useful as a nanomaterial for delivery or sequestration of atrazine
Infra-Red thermal image analysis for grapevines
Trabajo presentado en el 18th International Symposium of the Group of International Experts of vitivinicultural Systems for CoOperation (GIESCO 2013), celebrado en Oporto del 7 al 11 de julio de 2013.-- Número fuera de serie.Infrared thermal images (IRTI) have been used for grapevine research since the early 90’s. Even though
its promising results
in the
assessment of canopy stomatal conductance and plant
water status, from the beginning and recent research publications, it has not been fully
applied on a commercial scale yet. It is believed that the bottleneck for this technology is the lack
of reliable automation tools for IRTI
analysis. Accurate and reliable automation technique
s will allow the use of this technique to assess the spatial variability of physiological
processes within the canopy using infrared cameras
mounted on moving vehicles, drones, octocopters or robots. Automated analysis systems
are requirement of The Vineyard of The Future initiative, which is an international effort to establis
h fully monitored vineyards in the most
prominent viticultural and winemaking areas in the
world. In this work, a semi-automated IRTI analyses
performed using a code written in
MATLAB® for estimate dry and wet references excluding non-leaf temperatures was compared with evaporimeter (EvapoSensor, Skye Instruments Ltd, Powys, UK) measurements used to provide dry and wet references from IRTIs. Results obtained from this research
(grapevines cv. Tempranillo) showed good and statistically significant correlations between temperatur
e references obtained from IRTI
analysis and measured values. This work constitutes
one additional step forward to the implementation of thermal imaging as an automated
routine technique for physiological vineyard assess
ment from proximal sensing and unmanned aerial vehicles (UAV) platforms.The research leading to this report was supported by the Spanish project “STRESSIMAGING HPRN-CT-2002-00254” and Chilean projects CONICYT (Nº 79090035) and Programa de Investigación sobre Adaptación de la Agricultura al Cambio Climático - PIEI (Universidad de Talca).Peer Reviewe
Ecuaciones de Boussinesq: estimaciones uniformes en el tiempo de las aproximaciones de Galerkin espectrales
Obtenemos cotas para el error de las soluciones fuertes de las ecuaciones de Boussinesq que modelan los fluidos incompresibles y conductores de calor, suponiendo que dichas soluciones son condicionalmente asintĂłticamente estables. 
Spatial analysis of energy use and GHG emissions from cereal production in India
Agriculture contributes 18% of India's greenhouse gas (GHG) emissions. Yet, little is known about the energy requirements of individual crops, making it difficult to link nutrition-enhancing dietary changes to energy consumption and climate change. We estimate the energy and CO2 intensity of food grains (rice, wheat, sorghum, maize, pearl millet and finger millet) taking into account their irrigation requirements, water source, dependence on groundwater, yields, fertilizer and machinery inputs.
Rice is the most energy-intensive cereal, while millets are the least. Total energy use contributes 16% of GHG emissions for rice, due to its high methane emissions, and 56% for wheat. Fertilizer production and use dominates GHG emissions from all crops, contributing 52% of GHGs from cereals. Energy intensities vary by up to a factor of four across the country, due to varying water requirements, irrigation sources and groundwater table depths. The results suggest that replacing rice with other cereals has the potential to reduce energy consumption and GHGs, though the spatial variation of production shifts would influence the extent of this reduction and the possible trade-offs with total production
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