Transbilayer Pores Induced by Thickness Fluctuations

Thermally-induced fluctuations of individual phospholipids in a bilayer lipid membrane (BLM) are converted into collective motions due to the intermolecular interactions. Here, we demonstrate that transbilayer stochastic pores can be generated via collective thermal movements (CTM). Using the elastic theory of continuous media applied to smectic-A liquid crystals, we estimate the pore radius and the energetic requirements for pore appearance. Three types of thermally-induced transbilayer pores could be formed through BLMs: open and stable, open and unstable, and closed. In most of the situations, two open and stable pores with different radii could be generated. Notably, the two pores have the same generation probability. Unstable pores are possible to appear across thin bilayers that contain phospholipids with a large polar headgroup. Closed pores are present throughout the cases that we have inspected. The effects of hydrophobic thickness, polar headgroup size of phospholipids, temperature, surface tension, and elastic compression on the pore formation and pore stability have been examined as well.     

Multiscale modeling of cellular actin filaments: from atomistic molecular to coarse-grained dynamics

In this article, we present a computational multiscale model for the characterization of subcellular proteins. The model is encoded inside a simulation tool that builds coarse-grained (CG) force fields from atomistic simulations. Equilibrium molecular dynamics simulations on an all-atom model of the actin filament are performed. Then, using the statistical distribution of the distances between pairs of selected groups of atoms at the output of the MD simulations, the force field is parameterized using the Boltzmann inversion approach. This CG force field is further used to characterize the dynamics of the protein via Brownian dynamics simulations. This combination of methods into a single computational tool flow enables the simulation of actin filaments with length up to 400 nm, extending the time and length scales compared to state-of-the-art approaches. Moreover, the proposed multiscale modeling approach allows to investigate the relationship between atomistic structure and changes on the overall dynamics and mechanics of the filament and can be easily (i) extended to the characterization of other subcellular structures and (ii) used to investigate the cellular effects of molecular alterations due to pathological conditions.     

Lipid membrane domain formation and alamethicin aggregation studied by calorimetry, sound velocity measurements, and atomic force microscopy

An experimental study of phosphocholine membranes made from one lipid, from mixtures of DPPC and DLPC, and also from lipids and small amounts of alamethicin is presented. We used atomic force microscopy to investigate the spatial organization and structure of lipid domains and also of the defects induced by the peptide. Alamethicin was found to alter the state of lipids in the gel state in a way that domains of fluid lipids are formed close to the defects. Differential calorimetry revealed phase characteristics of the lipid mixtures and the effect of small amounts of alamethicin on the phase behavior. It was also shown that the sound velocity profiles of the membranes suspensions can be well calculated from the heat capacity traces of the samples. This result confirms the correlation between the mechanical properties and the specific heat of membrane systems.     

Spatial Controls of Pre–Euro-American Wind and Fire Disturbance in Northern Wisconsin (USA) Forest Landscapes

We elucidate spatial controls of wind and fire disturbance across northern Wisconsin (USA), where climatic and topographic gradients are not strong, using data from the original US Public Land Survey (PLS) notes. These records contain information on the location and extent of heavy windthrows and stand-replacing fires prior to Euro-American settlement. The spatial patterns of windthrow and fire were spatially clustered at all scales in this historical environment, with stronger associations at local than regional scales. Logistic regression shows environmental variables to have a strong influence on this pattern. In the case of heavy windthrow, environmental drivers of disturbance pattern are fairly consistent across the region. The effects of climate and vegetation are predominant at all scales, but effects are often indirect, with strong interactions between them. Interactions between these two drivers and soil characteristics are also sometimes present. In contrast, models of stand-replacing fire show simple and direct control within and across fire-prone landscapes of historical northern Wisconsin, with climate and physiography as the main factors explaining the distribution of fire disturbance. This simple and direct control is lost at the regional scale, where climate, physiographic, soil, and vegetation variables, along with interactions between them, are significant factors. Contrary to other regions, the topographic effects are generally not important in predicting either wind or fire disturbance. Our work suggests that, in landscapes that lack strong environmental patterning, climate maintains its role as a primary driver of these natural disturbances, but topography is replaced by interactions and feedbacks with other forms of environmental heterogeneity.     

Scaling Theory: Application to Marine Ornithology

The problem of scale has three components: (a) direct measurement is usually confined to small areas and brief periods, (b) the most pressing issues occur at the scale of ecosystems and decades, but (c) direct scale-up fails when pattern and process at small scales differ from those at larger scales. Recognition of this dilemma has grown exponentially since around 1980. The problem of scale is particularly acute for seabirds, which inhabit one of the most extensive habitats on the planet—the surface of the ocean. The application of power laws is a promising solution to the problem. Power laws have a long empirical tradition, are readily estimated from data, and now have a theoretical basis. Power law behavior (with nonintegral exponents) appears in systems with episodically warring exponential rates. In marine ornithology, examples of areas where power laws can be applied include patchy spatial distributions, the association of predator with prey, the scaling of food intake to body size, and fractal habitat structure. Scaling theory and power laws are applicable to a wide variety of ecosystem phenomena and dynamics, including fluxes of material and energy. Received 7 May 2001; accepted 12 April 2002.     

Mixtures of Associating and Non-associating Chains on Activated Surfaces: A Monte Carlo Approach

Abstract

The behavior of mixtures of associating and non-associating chains confined in pores with activated surfaces is studied by means of molecular simulation. The fluid molecules are modeled as a chain of four tangent Lennard-Jones spheres. Some of the chains have an additional associating square-well site placed in an end sphere. The activated surfaces of the slit pore are modeled via an integrated Lennard-Jones (10-4-3) potential with specific association sites protruding from the surface. We present Gibbs ensemble Monte Carlo simulation results for the partitioning of mixtures of chains in the bulk and confined phases for this particular model. The chain-wall association governs the adsorption behavior of the system. The preferential adsorption of associating chains is seen to strongly depend on temperature and pore width. Selectivities obtained are in the range of those seen in experiments of alkane-alkanol mixtures.     

Integrating Structural Information to Study the Dynamics of Protein-Protein Interactions in Cells

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Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine‐scale models to evaluate environmental heterogeneity may help detecting adaptation to micro‐habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1‐km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine‐scale topography. Using a large panel of DEM‐derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high‐resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.     

Quantification of root water uptake in soil using X‐ray computed tomography and image‐based modelling

Spatially averaged models of root–soil interactions are often used to calculate plant water uptake. Using a combination of X‐ray computed tomography (CT) and image‐based modelling, we tested the accuracy of this spatial averaging by directly calculating plant water uptake for young wheat plants in two soil types. The root system was imaged using X‐ray CT at 2, 4, 6, 8 and 12 d after transplanting. The roots were segmented using semi‐automated root tracking for speed and reproducibility. The segmented geometries were converted to a mesh suitable for the numerical solution of Richards' equation. Richards' equation was parameterized using existing pore scale studies of soil hydraulic properties in the rhizosphere of wheat plants. Image‐based modelling allows the spatial distribution of water around the root to be visualized and the fluxes into the root to be calculated. By comparing the results obtained through image‐based modelling to spatially averaged models, the impact of root architecture and geometry in water uptake was quantified. We observed that the spatially averaged models performed well in comparison to the image‐based models with <2% difference in uptake. However, the spatial averaging loses important information regarding the spatial distribution of water near the root system.