Visualizing single-molecule diffusion in mesoporous materials

Periodic mesoporous materials formed through the cooperative self-assembly of surfactants and framework building blocks can assume a variety of structures, and their widely tuneable properties make them attractive hosts for numerous applications. Because the molecular movement in the pore system is the most important and defining characteristic of porous materials, it is of interest to learn about this behaviour as a function of local structure. Generally, individual fluorescent dye molecules can be used as molecular beacons with which to explore the structure of--and the dynamics within--these porous hosts, and single-molecule fluorescence techniques provide detailed insights into the dynamics of various processes, ranging from biology to heterogeneous catalysis. However, optical microscopy methods cannot directly image the mesoporous structure of the host system accommodating the diffusing molecules, whereas transmission electron microscopy provides detailed images of the porous structure, but no dynamic information. It has therefore not been possible to 'see' how molecules diffuse in a real nanoscale pore structure. Here we present a combination of electron microscopic mapping and optical single-molecule tracking experiments to reveal how a single luminescent dye molecule travels through linear or strongly curved sections of a mesoporous channel system. In our approach we directly correlate porous structures detected by transmission electron microscopy with the diffusion dynamics of single molecules detected by optical microscopy. This opens up new ways of understanding the interactions of host and guest.     

Structural basis for synthesis of inflammatory mediators by human leukotriene C4 synthase

Cysteinyl leukotrienes are key mediators in inflammation and have an important role in acute and chronic inflammatory diseases of the cardiovascular and respiratory systems, in particular bronchial asthma. In the biosynthesis of cysteinyl leukotrienes, conversion of arachidonic acid forms the unstable epoxide leukotriene A4 (LTA4). This intermediate is conjugated with glutathione (GSH) to produce leukotriene C4 (LTC4) in a reaction catalysed by LTC4 synthase: this reaction is the key step in cysteinyl leukotriene formation. Here we present the crystal structure of the human LTC4 synthase in its apo and GSH-complexed forms to 2.00 and 2.15 A resolution, respectively. The structure reveals a homotrimer, where each monomer is composed of four transmembrane segments. The structure of the enzyme in complex with substrate reveals that the active site enforces a horseshoe-shaped conformation on GSH, and effectively positions the thiol group for activation by a nearby arginine at the membrane-enzyme interface. In addition, the structure provides a model for how the omega-end of the lipophilic co-substrate is pinned at one end of a hydrophobic cleft, providing a molecular 'ruler' to align the reactive epoxide at the thiol of glutathione. This provides new structural insights into the mechanism of LTC4 formation, and also suggests that the observed binding and activation of GSH might be common for a family of homologous proteins important for inflammatory and detoxification responses.     

Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme

Cryptic variation is caused by the robustness of phenotypes to mutations. Cryptic variation has no effect on phenotypes in a given genetic or environmental background, but it can have effects after mutations or environmental change. Because evolutionary adaptation by natural selection requires phenotypic variation, phenotypically revealed cryptic genetic variation may facilitate evolutionary adaptation. This is possible if the cryptic variation happens to be pre-adapted, or "exapted", to a new environment, and is thus advantageous once revealed. However, this facilitating role for cryptic variation has not been proven, partly because most pertinent work focuses on complex phenotypes of whole organisms whose genetic basis is incompletely understood. Here we show that populations of RNA enzymes with accumulated cryptic variation adapt more rapidly to a new substrate than a population without cryptic variation. A detailed analysis of our evolving RNA populations in genotype space shows that cryptic variation allows a population to explore new genotypes that become adaptive only in a new environment. Our observations show that cryptic variation contains new genotypes pre-adapted to a changed environment. Our results highlight the positive role that robustness and epistasis can have in adaptive evolution.     

Acetylation-dependent regulation of endothelial Notch signalling by the SIRT1 deacetylase

Notch signalling is a key intercellular communication mechanism that is essential for cell specification and tissue patterning, and which coordinates critical steps of blood vessel growth. Although subtle alterations in Notch activity suffice to elicit profound differences in endothelial behaviour and blood vessel formation, little is known about the regulation and adaptation of endothelial Notch responses. Here we report that the NAD(+)-dependent deacetylase SIRT1 acts as an intrinsic negative modulator of Notch signalling in endothelial cells. We show that acetylation of the Notch1 intracellular domain (NICD) on conserved lysines controls the amplitude and duration of Notch responses by altering NICD protein turnover. SIRT1 associates with NICD and functions as a NICD deacetylase, which opposes the acetylation-induced NICD stabilization. Consequently, endothelial cells lacking SIRT1 activity are sensitized to Notch signalling, resulting in impaired growth, sprout elongation and enhanced Notch target gene expression in response to DLL4 stimulation, thereby promoting a non-sprouting, stalk-cell-like phenotype. In vivo, inactivation of Sirt1 in zebrafish and mice causes reduced vascular branching and density as a consequence of enhanced Notch signalling. Our findings identify reversible acetylation of the NICD as a molecular mechanism to adapt the dynamics of Notch signalling, and indicate that SIRT1 acts as rheostat to fine-tune endothelial Notch responses.     

Oxysterols direct immune cell migration via EBI2

Epstein-Barr virus-induced gene 2 (EBI2, also known as GPR183) is a G-protein-coupled receptor that is required for humoral immune responses; polymorphisms in the receptor have been associated with inflammatory autoimmune diseases. The natural ligand for EBI2 has been unknown. Here we describe the identification of 7α,25-dihydroxycholesterol (also called 7α,25-OHC or 5-cholesten-3β,7α,25-triol) as a potent and selective agonist of EBI2. Functional activation of human EBI2 by 7α,25-OHC and closely related oxysterols was verified by monitoring second messenger readouts and saturable, high-affinity radioligand binding. Furthermore, we find that 7α,25-OHC and closely related oxysterols act as chemoattractants for immune cells expressing EBI2 by directing cell migration in vitro and in vivo. A critical enzyme required for the generation of 7α,25-OHC is cholesterol 25-hydroxylase (CH25H). Similar to EBI2 receptor knockout mice, mice deficient in CH25H fail to position activated B cells within the spleen to the outer follicle and mount a reduced plasma cell response after an immune challenge. This demonstrates that CH25H generates EBI2 biological activity in vivo and indicates that the EBI2-oxysterol signalling pathway has an important role in the adaptive immune response.     

Structure of a nanobody-stabilized active state of the β(2) adrenoceptor

G protein coupled receptors (GPCRs) exhibit a spectrum of functional behaviours in response to natural and synthetic ligands. Recent crystal structures provide insights into inactive states of several GPCRs. Efforts to obtain an agonist-bound active-state GPCR structure have proven difficult due to the inherent instability of this state in the absence of a G protein. We generated a camelid antibody fragment (nanobody) to the human β(2) adrenergic receptor (β(2)AR) that exhibits G protein-like behaviour, and obtained an agonist-bound, active-state crystal structure of the receptor-nanobody complex. Comparison with the inactive β(2)AR structure reveals subtle changes in the binding pocket; however, these small changes are associated with an 11?? outward movement of the cytoplasmic end of transmembrane segment 6, and rearrangements of transmembrane segments 5 and 7 that are remarkably similar to those observed in opsin, an active form of rhodopsin. This structure provides insights into the process of agonist binding and activation.     

A disinhibitory microcircuit for associative fear learning in the auditory cortex

Learning causes a change in how information is processed by neuronal circuits. Whereas synaptic plasticity, an important cellular mechanism, has been studied in great detail, we know much less about how learning is implemented at the level of neuronal circuits and, in particular, how interactions between distinct types of neurons within local networks contribute to the process of learning. Here we show that acquisition of associative fear memories depends on the recruitment of a disinhibitory microcircuit in the mouse auditory cortex. Fear-conditioning-associated disinhibition in auditory cortex is driven by foot-shock-mediated cholinergic activation of layer 1 interneurons, in turn generating inhibition of layer 2/3 parvalbumin-positive interneurons. Importantly, pharmacological or optogenetic block of pyramidal neuron disinhibition abolishes fear learning. Together, these data demonstrate that stimulus convergence in the auditory cortex is necessary for associative fear learning to complex tones, define the circuit elements mediating this convergence and suggest that layer-1-mediated disinhibition is an important mechanism underlying learning and information processing in neocortical circuits.     

Role of sulphuric acid, ammonia and galactic cosmic rays in atmospheric aerosol nucleation

Atmospheric aerosols exert an important influence on climate through their effects on stratiform cloud albedo and lifetime and the invigoration of convective storms. Model calculations suggest that almost half of the global cloud condensation nuclei in the atmospheric boundary layer may originate from the nucleation of aerosols from trace condensable vapours, although the sensitivity of the number of cloud condensation nuclei to changes of nucleation rate may be small. Despite extensive research, fundamental questions remain about the nucleation rate of sulphuric acid particles and the mechanisms responsible, including the roles of galactic cosmic rays and other chemical species such as ammonia. Here we present the first results from the CLOUD experiment at CERN. We find that atmospherically relevant ammonia mixing ratios of 100 parts per trillion by volume, or less, increase the nucleation rate of sulphuric acid particles more than 100-1,000-fold. Time-resolved molecular measurements reveal that nucleation proceeds by a base-stabilization mechanism involving the stepwise accretion of ammonia molecules. Ions increase the nucleation rate by an additional factor of between two and more than ten at ground-level galactic-cosmic-ray intensities, provided that the nucleation rate lies below the limiting ion-pair production rate. We find that ion-induced binary nucleation of H(2)SO(4)-H(2)O can occur in the mid-troposphere but is negligible in the boundary layer. However, even with the large enhancements in rate due to ammonia and ions, atmospheric concentrations of ammonia and sulphuric acid are insufficient to account for observed boundary-layer nucleation.     

Forecasting Government Bond Yields with Neural Networks Considering Cointegration

This paper discusses techniques that might be helpful in predicting interest rates and tries to evaluate a new hybrid forecasting approach. Results of examining government bond yields in Germany and France reported in this study indicate that a hybrid forecasting approach which combines techniques of cointegration analysis with neural network (NN) forecasting models can produce superior results to the use of NN forecasting models alone. The findings documented in this paper could be a consequence of the fact that examining differenced data under certain conditions will lead to a loss of information and that the inclusion of the error correction term from the cointegration model can help to cope with this problem. The paper also discusses some possibly interesting directions for further research. Copyright © 2015 John Wiley & Sons, Ltd.