Coulomb drag between one-dimensional conductors

We have analyzed Coulomb drag between currents of interacting electrons in two parallel one-dimensional conductors of finite length $L$ attached to external reservoirs. For strong coupling, the relative fluctuations of electron density in the conductors acquire energy gap $M$. At energies larger than $\Gamma = const \times v_- \exp (-LM/v_-)/L + \Gamma_{+}$, where $\Gamma_{+}$ is the impurity scattering rate, and for $L>v_-/M$, where $v_-$ is the fluctuation velocity, the gap leads to an ``ideal'' drag with almost equal currents in the conductors. At low energies the drag is suppressed by coherent instanton tunneling, and the zero-temperature transconductance vanishes, indicating the Fermi liquid behavior.Comment: 5 twocolumn pages in RevTex, added 1 eps-Figure and calculation of trans-resistanc

Thermodynamic Signature of a Two-Dimensional Metal-Insulator Transition

We present a study of the compressibility, K, of a two-dimensional hole system which exhibits a metal-insulator phase transition at zero magnetic field. It has been observed that dK/dp changes sign at the critical density for the metal-insulator transition. Measurements also indicate that the insulating phase is incompressible for all values of B. Finally, we show how the phase transition evolves as the magnetic field is varied and construct a phase diagram in the density-magnetic field plane for this system.Comment: 4 pages, 4 figures, submitted to Physical Review Letters; version 1 is identical to version 2 but didn't compile properl

Otopathogenic Pseudomonas aeruginosa Enters and Survives Inside Macrophages

Otitis media (OM) is a broad term describing a group of infectious and inflammatory disorders of the middle ear. Despite antibiotic therapy, acute OM can progress to chronic suppurative otitis media (CSOM) characterized by ear drum perforation and purulent discharge. Pseudomonas aeruginosa is the most common pathogen associated with CSOM. Although, macrophages play an important role in innate immune responses but their role in the pathogenesis of P. aeruginosa-induced CSOM is not known. The objective of this study is to examine the interaction of P. aeruginosa with primary macrophages. We observed that P. aeruginosa enters and multiplies inside human and mouse primary macrophages. This bacterial entry in macrophages requires both microtubule and actin dependent processes. Transmission electron microscopy demonstrated that P. aeruginosa was present in membrane bound vesicles inside macrophages. Interestingly, deletion of oprF expression in P. aeruginosa abrogates its ability to survive inside macrophages. Our results suggest that otopathogenic P. aeruginosa entry and survival inside macrophages is OprF-dependent. The survival of bacteria inside macrophages will lead to evasion of killing and this lack of pathogen clearance by phagocytes contributes to the persistence of infection in CSOM. Understanding host–pathogen interaction will provide novel avenues to design effective treatment modalities against OM

Unpredictability of metabolism—the key role of metabolomics science in combination with next-generation genome sequencing

Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype–phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N. This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science—the quantitative measurement of metabolism in conjunction with metabolic modelling—is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype–phenotype relationship

Adjustment of photosynthetic activity to drought and fluctuating light in wheat

Drought is a major cause of losses in crop yield. Under field conditions, plants exposed to drought are usually also experiencing rapid changes in light intensity. Accordingly, plants need to acclimate to both, drought and light stress. Two crucial mechanisms in plant acclimation to changes in light conditions comprise thylakoid protein phosphorylation and dissipation of light energy as heat by non-photochemical quenching (NPQ). Here, we analyzed the acclimation efficacy of two different wheat varieties, by applying fluctuating light for analysis of plants, which had been subjected to a slowly developing drought stress as it usually occurs in the field. This novel approach allowed us to distinguish four drought phases, which are critical for grain yield, and to discover acclimatory responses which are independent of photodamage. In short-term, under fluctuating light, the slowdown of NPQ relaxation adjusts the photosynthetic activity to the reduced metabolic capacity. In long-term, the photosynthetic machinery acquires a drought-specific configuration by changing the PSII-LHCII phosphorylation pattern together with protein stoichiometry. Therefore, the fine-tuning of NPQ relaxation and PSII-LHCII phosphorylation pattern represent promising traits for future crop breeding strategies

Comprehensive tissue-specific proteome analysis of drought stress responses in Pennisetum glaucum (L.) R. Br. (Pearl millet)

Pearl millet is the fifth most important cereal crop worldwide and cultivated especially by small holder farmers in arid and semi-arid regions because of its drought and salt tolerance. The molecular mechanisms of drought stress tolerance in Pennisetum remain elusive. We have used a shotgun proteomics approach to investigate protein signatures from different tissues under drought and control conditions. Drought stressed plants showed significant changes in stomatal conductance and increased root growth compared to the control plants. Root, leaf and seed tissues were harvested and 2281 proteins were identified and quantified in total. Leaf tissue showed the largest number of significant changes (120), followed by roots (25) and seeds (10). Increased levels of root proteins involved in cell wall-, lipid-, secondary- and signaling metabolism and the concomitantly observed increased root length point to an impaired shoot–root communication under drought stress. The harvest index (HI) showed a significant reduction under drought stress. Proteins with a high correlation to the HI were identified using sparse partial least square (sPLS) analysis. Considering the importance of Pearl millet as a stress tolerant food crop, this study provides a first reference data set for future investigations of the underlying molecular mechanisms

Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

<p>Abstract</p> <p>Background</p> <p>Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites) has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites.</p> <p>Results</p> <p>We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D) structural information available in the protein data bank (PDB) and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information.</p> <p>Conclusion</p> <p>While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as relevant for the recognition of kinases and their cognate target sites and can be used for an improved prediction of phosphorylation sites. A web-based service (Phos3D) implementing the developed structure-based P-site prediction method has been made available at <url>http://phos3d.mpimp-golm.mpg.de</url>.</p

Natural products in drug discovery: advances and opportunities

Natural products and their structural analogues have historically made a major contribution to pharmacotherapy, especially for cancer and infectious diseases. Nevertheless, natural products also present challenges for drug discovery, such as technical barriers to screening, isolation, characterization and optimization, which contributed to a decline in their pursuit by the pharmaceutical industry from the 1990s onwards. In recent years, several technological and scientific developments — including improved analytical tools, genome mining and engineering strategies, and microbial culturing advances — are addressing such challenges and opening up new opportunities. Consequently, interest in natural products as drug leads is being revitalized, particularly for tackling antimicrobial resistance. Here, we summarize recent technological developments that are enabling natural product-based drug discovery, highlight selected applications and discuss key opportunities

Magnetoresistance of one-dimensional subbands in tunnel-coupled double quantum wires

We study the low-temperature in-plane magnetoresistance of tunnel-coupled quasi-one-dimensional quantum wires. The wires are defined by two pairs of mutually aligned split gates on opposite sides of a < 1 micron thick AlGaAs/GaAs double quantum well heterostructure, allowing independent control of their widths. In the ballistic regime, when both wires are defined and the field is perpendicular to the current, a large resistance peak at ~6 Tesla is observed with a strong gate voltage dependence. The data is consistent with a counting model whereby the number of subbands crossing the Fermi level changes with field due to the formation of an anticrossing in each pair of 1D subbands