Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation

The Earth’s inner core grows by the freezing of liquid iron at its surface. The point in history at which this process initiated marks a step-change in the thermal evolution of the planet. Recent computational and experimental studies1,2,3,4,5 have presented radically differing estimates of the thermal conductivity of the Earth’s core, resulting in estimates of the timing of inner-core nucleation ranging from less than half a billion to nearly two billion years ago. Recent inner-core nucleation (high thermal conductivity) requires high outer-core temperatures in the early Earth that complicate models of thermal evolution. The nucleation of the core leads to a different convective regime6 and potentially different magnetic field structures that produce an observable signal in the palaeomagnetic record and allow the date of inner-core nucleation to be estimated directly. Previous studies searching for this signature have been hampered by the paucity of palaeomagnetic intensity measurements, by the lack of an effective means of assessing their reliability, and by shorter-timescale geomagnetic variations. Here we examine results from an expanded Precambrian database of palaeomagnetic intensity measurements7 selected using a new set of reliability criteria8. Our analysis provides intensity-based support for the dominant dipolarity of the time-averaged Precambrian field, a crucial requirement for palaeomagnetic reconstructions of continents. We also present firm evidence for the existence of very long-term variations in geomagnetic strength. The most prominent and robust transition in the record is an increase in both average field strength and variability that is observed to occur between a billion and 1.5 billion years ago. This observation is most readily explained by the nucleation of the inner core occurring during this interval9; the timing would tend to favour a modest value of core thermal conductivity and supports a simple thermal evolution model for the Earth

Chloride Ions in the Pore of Glycine and GABA Channels Shape the Time Course and Voltage Dependence of Agonist Currents

In the vertebrate CNS, fast synaptic inhibition is mediated by GABA and glycine receptors. We recently reported that the time course of these synaptic currents is slower when intracellular chloride is high. Here we extend these findings to measure the effects of both extracellular and intracellular chloride on the deactivation of glycine and GABA currents at both negative and positive holding potentials. Currents were elicited by fast agonist application to outside-out patches from HEK-293 cells expressing rat glycine or GABA receptors. The slowing effect of high extracellular chloride on current decay was detectable only in low intracellular chloride (4 mM). Our main finding is that glycine and GABA receptors "sense" chloride concentrations because of interactions between the M2 pore-lining domain and the permeating ions. This hypothesis is supported by the observation that the sensitivity of channel gating to intracellular chloride is abolished if the channel is engineered to become cation selective or if positive charges in the external pore vestibule are eliminated by mutagenesis. The appropriate interaction between permeating ions and channel pore is also necessary to maintain the channel voltage sensitivity of gating, which prolongs current decay at depolarized potentials. Voltage dependence is abolished by the same mutations that suppress the effect of intracellular chloride and also by replacing chloride with another permeant ion, thiocyanate. These observations suggest that permeant chloride affects gating by a foot-in-the-door effect, binding to a channel site with asymmetrical access from the intracellular and extracellular sides of the membrane

Evaluation of the multispecimen parallel differential pTRM method: a test on historical lavas from Iceland and Mexico

Accepted versio

Deciphering the folding kinetics of transmembrane helical proteins

Nearly a quarter of genomic sequences and almost half of all receptors that are likely to be targets for drug design are integral membrane proteins. Understanding the detailed mechanisms of the folding of membrane proteins is a largely unsolved, key problem in structural biology. Here, we introduce a general model and use computer simulations to study the equilibrium properties and the folding kinetics of a $C_{\alpha}$-based two helix bundle fragment (comprised of 66 amino-acids) of Bacteriorhodopsin. Various intermediates are identified and their free energy are calculated toghether with the free energy barrier between them. In 40% of folding trajectories, the folding rate is considerably increased by the presence of non-obligatory intermediates acting as traps. In all cases, a substantial portion of the helices is rapidly formed. This initial stage is followed by a long period of consolidation of the helices accompanied by their correct packing within the membrane. Our results provide the framework for understanding the variety of folding pathways of helical transmembrane proteins

High-throughput isolation and characterization of untagged membrane protein complexes: outer membrane complexes of Desulfovibrio vulgaris.

Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein-protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms

Paleoproterozoic Geomagnetic Field Strength From the Avanavero Mafic Sills, Amazonian Craton, Brazil

A recent hypothesis has suggested that Earth's inner core nucleated during the Mesoproterozoic, as evidenced by a rapid increase in the paleointensity (ancient geomagnetic field intensity) record; however, paleointensity data during the Paleoproterozoic and Mesoproterozoic period are limited. To address this problem, we have determined paleointensity from samples from three Paleoproterozoic Avanavero mafic sills (Amazonian Craton, Brazil): Cotingo, 1782 Ma, Puiuà 1788, and Pedra Preta, 1795 Ma. We adopted a multi-protocol approach for paleointensity estimates combining Thellier-type IZZI and LTD-IZZI methods, and the non-heating Preisach protocol. We obtained an average VDM value of 1.3 ± 0.7 × 1022Am2 (Cotingo) of 2.0 ± 0.4 × 1022Am2 (Puiuà) and 6 ± 4 × 1022Am2 (Pedra Preta); it is argued that the Cotingo estimate is the most robust. Our results are the first data from the upper Paleoproterozoic for South America and are comparable to data available from other regions and similar periods. The new data do not invalidate the hypothesis of that Earth's inner core nucleated during the Mesoproterozoic

Covariant Giant Gaussian Process Models With Improved Reproduction of Palaeosecular Variation

A commonly used family of statistical magnetic field models is based on a giant Gaussian process (GGP), which assumes each Gauss coefficient can be realized from an independent normal distribution. GGP models are capable of generating suites of plausible Gauss coefficients, allowing for palaeomagnetic data to be tested against the expected distribution arising from a time‐averaged geomagnetic field. However, existing GGP models do not simultaneously reproduce the distribution of field strength and palaeosecular variation estimates reported for the past 10 million years and tend to underpredict virtual geomagnetic pole (VGP) dispersion at high latitudes unless trade‐offs are made to the fit at lower latitudes. Here we introduce a new family of GGP models, BB18 and BB18.Z3 (the latter includes non‐zero‐mean zonal terms for spherical harmonic degrees 2 and 3). Our models are distinct from prior GGP models by simultaneously treating the axial dipole variance separately from higher degree terms, applying an odd‐even variance structure, and incorporating a covariance between certain Gauss coefficients. Covariance between Gauss coefficients, a property both expected from dynamo theory and observed in numerical dynamo simulations, has not previously been included in GGP models. Introducing covariance between certain Gauss coefficients inferred from an ensemble of “Earth‐like” dynamo simulations and predicted by theory yields a reduced misfit to VGP dispersion, allowing for GGP models which generate improved reproductions of the distribution of field strengths and palaeosecular variation observed for the last 10 million years

JGromacs: A Java Package for Analyzing Protein Simulations

UNLABELLED: In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. AVAILABILITY: JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license

Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.

BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell