Fluctuation-enhanced electric conductivity in electrolyte solutions

In this letter we analyze the effects of an externally applied electric field on thermal fluctuations for a fluid containing charged species. We show in particular that the fluctuating Poisson-Nernst-Planck equations for charged multispecies diffusion coupled with the fluctuating fluid momentum equation, result in enhanced charge transport. Although this transport is advective in nature, it can macroscopically be represented as electrodiffusion with renormalized electric conductivity. We calculate the renormalized electric conductivity by deriving and integrating the structure factor coefficients of the fluctuating quantities and show that the renormalized electric conductivity and diffusion coefficients are consistent although they originate from different noise terms. In addition, the fluctuating hydrodynamics approach recovers the electrophoretic and relaxation corrections obtained by Debye-Huckel-Onsager theory, and provides a quantitative theory that predicts a non-zero cross-diffusion Maxwell-Stefan coefficient that agrees well with experimental measurements. Finally, we show that strong applied electric fields result in anisotropically enhanced velocity fluctuations and reduced fluctuations of salt concentrations.Comment: 12 pages, 1 figur

Low Mach Number Fluctuating Hydrodynamics for Electrolytes

We formulate and study computationally the low Mach number fluctuating hydrodynamic equations for electrolyte solutions. We are interested in studying transport in mixtures of charged species at the mesoscale, down to scales below the Debye length, where thermal fluctuations have a significant impact on the dynamics. Continuing our previous work on fluctuating hydrodynamics of multicomponent mixtures of incompressible isothermal miscible liquids (A. Donev, et al., Physics of Fluids, 27, 3, 2015), we now include the effect of charged species using a quasielectrostatic approximation. Localized charges create an electric field, which in turn provides additional forcing in the mass and momentum equations. Our low Mach number formulation eliminates sound waves from the fully compressible formulation and leads to a more computationally efficient quasi-incompressible formulation. We demonstrate our ability to model saltwater (NaCl) solutions in both equilibrium and nonequilibrium settings. We show that our algorithm is second-order in the deterministic setting, and for length scales much greater than the Debye length gives results consistent with an electroneutral/ambipolar approximation. In the stochastic setting, our model captures the predicted dynamics of equilibrium and nonequilibrium fluctuations. We also identify and model an instability that appears when diffusive mixing occurs in the presence of an applied electric field.Comment: 37 pages, 5 figure

Novel components of the Toxoplasma inner membrane complex revealed by BioID.

UNLABELLED:The inner membrane complex (IMC) of Toxoplasma gondii is a peripheral membrane system that is composed of flattened alveolar sacs that underlie the plasma membrane, coupled to a supporting cytoskeletal network. The IMC plays important roles in parasite replication, motility, and host cell invasion. Despite these central roles in the biology of the parasite, the proteins that constitute the IMC are largely unknown. In this study, we have adapted a technique named proximity-dependent biotin identification (BioID) for use in T. gondii to identify novel components of the IMC. Using IMC proteins in both the alveoli and the cytoskeletal network as bait, we have uncovered a total of 19 new IMC proteins in both of these suborganellar compartments, two of which we functionally evaluate by gene knockout. Importantly, labeling of IMC proteins using this approach has revealed a group of proteins that localize to the sutures of the alveolar sacs that have been seen in their entirety in Toxoplasma species only by freeze fracture electron microscopy. Collectively, our study greatly expands the repertoire of known proteins in the IMC and experimentally validates BioID as a strategy for discovering novel constituents of specific cellular compartments of T. gondii. IMPORTANCE:The identification of binding partners is critical for determining protein function within cellular compartments. However, discovery of protein-protein interactions within membrane or cytoskeletal compartments is challenging, particularly for transient or unstable interactions that are often disrupted by experimental manipulation of these compartments. To circumvent these problems, we adapted an in vivo biotinylation technique called BioID for Toxoplasma species to identify binding partners and proximal proteins within native cellular environments. We used BioID to identify 19 novel proteins in the parasite IMC, an organelle consisting of fused membrane sacs and an underlying cytoskeleton, whose protein composition is largely unknown. We also demonstrate the power of BioID for targeted discovery of proteins within specific compartments, such as the IMC cytoskeleton. In addition, we uncovered a new group of proteins localizing to the alveolar sutures of the IMC. BioID promises to reveal new insights on protein constituents and interactions within cellular compartments of Toxoplasma

ECOSSE: Estimating Carbon in Organic Soils - Sequestration and Emissions: Final Report

Background Climate change, caused by greenhouse gas ( GHG) emissions, is one of the most serious threats facing our planet, and is of concern at both UK and devolved administration levels. Accurate predictions for the effects of changes in climate and land use on GHG emissions are vital for informing land use policy. Models which are currently used to predict differences in soil carbon (C) and nitrogen (N) caused by these changes, have been derived from those based on mineral soils or deep peat. None of these models is entirely satisfactory for describing what happens to organic soils following land-use change. Reports of Scottish GHG emissions have revealed that approximately 15% of Scotland's total emissions come from land use changes on Scotland's high carbon soils; the figure is much lower for Wales. It is therefore important to reduce the major uncertainty in assessing the carbon store and flux from land use change on organic soils, especially those which are too shallow to be deep peats but still contain a large reserve of C. In order to predict the response of organic soils to external change we need to develop a model that reflects more accurately the conditions of these soils. The development of a model for organic soils will help to provide more accurate values of net change to soil C and N in response to changes in land use and climate and may be used to inform reporting to UKGHG inventories. Whilst a few models have been developed to describe deep peat formation and turnover, none have so far been developed suitable for examining the impacts of land-use and climate change on the types of organic soils often subject to land-use change in Scotland and Wales. Organic soils subject to land-use change are often (but not exclusively) characterised by a shallower organic horizon than deep peats (e.g. organo-mineral soils such as peaty podzols and peaty gleys). The main aim of the model developed in this project was to simulate the impacts of land-use and climate change in these types of soils. The model is, a) be driven by commonly available meteorological data and soil descriptions, b) able to simulate and predict C and N turnover in organic soils, c) able to predict the impacts of land-use change and climate change on C and N stores in organic soils in Scotland and Wales. In addition to developing the model, we have undertaken a number of other modelling exercises, literature searches, desk studies, data base exercises, and experimentation to answer a range of other questions associated with the responses of organic soils in Scotland and Wales to climate and land-use change. Aims of the ECOSSE project The aims of the study were: To develop a new model of C and N dynamics that reflects conditions in organic soils in Scotland and Wales and predicts their likely responses to external factors To identify the extent of soils that can be considered organic in Scotland and Wales and provide an estimate of the carbon contained within them To predict the contribution of CO 2, nitrous oxide and methane emissions from organic soils in Scotland and Wales, and provide advice on how changes in land use and climate will affect the C and N balance In order to fulfil these aims, the project was broken down into modules based on these objectives and the report uses that structure. The first aim is covered by module 2, the second aim by module 1, and the third aim by modules 3 to 8. Many of the modules are inter-linked. Objectives of the ECOSSE project The main objectives of the project were to: Describe the distribution of organic soils in Scotland and Wales and provide an estimate of the C contained in them Develop a model to simulate C and N cycling in organic soils and provide predictions as to how they will respond to land-use, management and climate change using elements of existing peat, mineral and forest soil models Provide predictive statements on the effects of land-use and climate change on organic soils and the relationships to GHG emissions, including CO 2, nitrous oxide and methane. Provide predictions on the effects of land use change and climate change on the release of Dissolved Organic Matter from organic soils Provide estimates of C loss from scenarios of accelerated erosion of organic soils Suggest best options for mitigating C and N loss from organic soils Provide guidelines on the likely effects of changing land-use from grazing or semi-natural vegetation to forestry on C and N in organic soils Use the land-use change data derived from the Countryside Surveys of Scotland and Wales to provide predictive estimates for changes to C and N balance in organic soils over time

MERAV: a tool for comparing gene expression across human tissues and cell types

The oncogenic transformation of normal cells into malignant, rapidly proliferating cells requires major alterations in cell physiology. For example, the transformed cells remodel their metabolic processes to supply the additional demand for cellular building blocks. We have recently demonstrated essential metabolic processes in tumor progression through the development of a methodological analysis of gene expression. Here, we present the Metabolic gEne RApid Visualizer (MERAV, http://merav.wi.mit.edu), a web-based tool that can query a database comprising ∼4300 microarrays, representing human gene expression in normal tissues, cancer cell lines and primary tumors. MERAV has been designed as a powerful tool for whole genome analysis which offers multiple advantages: one can search many genes in parallel; compare gene expression among different tissue types as well as between normal and cancer cells; download raw data; and generate heatmaps; and finally, use its internal statistical tool. Most importantly, MERAV has been designed as a unique tool for analyzing metabolic processes as it includes matrixes specifically focused on metabolic genes and is linked to the Kyoto Encyclopedia of Genes and Genomes pathway search.United States. National Institutes of Health (CA103866)United States. National Institutes of Health (AI47389)Life Sciences Research FoundationMassachusetts Institute of Technology. Ludwig Center for Molecular OncologyHoward Hughes Medical Institut