Evolution of T Cell Responses during Measles Virus Infection and RNA Clearance

Measles is an acute viral disease associated both with immune suppression and development of life-long immunity. Clearance of measles virus (MeV) involves rapid elimination of infectious virus during the rash followed by slow elimination of viral RNA. To characterize cellular immune responses during recovery, we analyzed the appearance, specificity and function of MeV-specific T cells for 6 months after respiratory infection of rhesus macaques with wild type MeV. IFN-γ and IL-17-producing cells specific for the hemagglutinin and nucleocapsid proteins appeared in circulation in multiple waves approximately 2-3, 8 and 18-24 weeks after infection. IFN-γ-secreting cells were most abundant early and IL-17-secreting cells late. Both CD4 and CD8 T cells were sources of IFN-γ and IL-17, and IL-17-producing cells expressed RORγt. Therefore, the cellular immune response evolves during MeV clearance to produce functionally distinct subsets of MeV-specific CD4 and CD8 T cells at different times after infection

A 7 Tesla fMRI Study of Amygdala Responses to Fearful Faces

The amygdalae are involved in the perception of emotions such as happiness, anger and fear. Because of their proximity to the sinuses, the image signal intensity in T2* weighted fMRI data is often affected by signal loss due to through-slice dephasing, especially at high field strength. In this study, the feasibility of fMRI in the amygdalae at 7 Tesla was investigated. A paradigm based on the presentation of fearful faces was used for stimulation. Previously, opposite effects have been found for presentation of averted and direct gaze fearful faces. Here, we show that (1) sufficiently high temporal SNR values are reached in the amygdalae for detection of small BOLD signal changes and (2) that the BOLD signal in the amygdalae for presentation of a direct or averted gaze in a fearful face depends on stimulus duration

The Metal Ion Requirements of \u3cem\u3eArabidopsis thaliana\u3c/em\u3e Glx2-2 for Catalytic Activity

In an effort to better understand the structure, metal content, the nature of the metal centers, and enzyme activity of Arabidopsis thaliana Glx2-2, the enzyme was overexpressed, purified, and characterized using metal analyses, kinetics, and UV–vis, EPR, and 1H NMR spectroscopies. Glx2-2-containing fractions that were purple, yellow, or colorless were separated during purification, and the differently colored fractions were found to contain different amounts of Fe and Zn(II). Spectroscopic analyses of the discrete fractions provided evidence for Fe(II), Fe(III), Fe(III)–Zn(II), and antiferromagnetically coupled Fe(II)–Fe(III) centers distributed among the discrete Glx2-2-containing fractions. The individual steady-state kinetic constants varied among the fractionated species, depending on the number and type of metal ion present. Intriguingly, however, the catalytic efficiency constant, k cat/K m, was invariant among the fractions. The value of k cat/K m governs the catalytic rate at low, physiological substrate concentrations. We suggest that the independence of k cat/K m on the precise makeup of the active-site metal center is evolutionarily related to the lack of selectivity for either Fe versus Zn(II) or Fe(II) versus Fe(III), in one or more metal binding sites

CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab

CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS models. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output

The Landlab v1.0 OverlandFlow component: a Python tool for computing shallow-water flow across watersheds

Representation of flowing water in landscape evolution models (LEMs) is often simplified compared to hydrodynamic models, as LEMs make assumptions reducing physical complexity in favor of computational efficiency. The Landlab modeling framework can be used to bridge the divide between complex runoff models and more traditional LEMs, creating a new type of framework not commonly used in the geomorphology or hydrology communities. Landlab is a Python-language library that includes tools and process components that can be used to create models of Earth-surface dynamics over a range of temporal and spatial scales. The Landlab OverlandFlow component is based on a simplified inertial approximation of the shallow water equations, following the solution of de Almeida et al. (2012). This explicit two-dimensional hydrodynamic algorithm simulates a flood wave across a model domain, where water discharge and flow depth are calculated at all locations within a structured (raster) grid. Here we illustrate how the OverlandFlow component contained within Landlab can be applied as a simplified event-based runoff model and how to couple the runoff model with an incision model operating on decadal timescales. Examples of flow routing on both real and synthetic landscapes are shown. Hydrographs from a single storm at multiple locations in the Spring Creek watershed, Colorado, USA, are illustrated, along with a map of shear stress applied on the land surface by flowing water. The OverlandFlow component can also be coupled with the Landlab DetachmentLtdErosion component to illustrate how the nonsteady flow routing regime impacts incision across a watershed. The hydrograph and incision results are compared to simulations driven by steady-state runoff. Results from the coupled runoff and incision model indicate that runoff dynamics can impact landscape relief and channel concavity, suggesting that on landscape evolution timescales, the OverlandFlow model may lead to differences in simulated topography in comparison with traditional methods. The exploratory test cases described within demonstrate how the OverlandFlow component can be used in both hydrologic and geomorphic applications

Human Glyoxalase II Contains an Fe(II)Zn(II) Center but Is Active as a Mononuclear Zn(II) Enzyme

Human glyoxalase II (Glx2) was overexpressed in rich medium and in minimal medium containing zinc, iron, or cobalt, and the resulting Glx2 analogues were characterized using metal analyses, steady-state and pre-steady-state kinetics, and NMR and EPR spectroscopies to determine the nature of the metal center in the enzyme. Recombinant human Glx2 tightly binds nearly 1 equiv each of Zn(II) and Fe. In contrast to previous reports, this study demonstrates that an analogue containing 2 equiv of Zn(II) cannot be prepared. EPR studies suggest that most of the iron in recombinant Glx2 is Fe(II). NMR studies show that Fe(II) binds to the consensus Zn2 site in Glx2 and that this site can also bind Co(II) and Ni(II), suggesting that Zn(II) binds to the consensus Zn1 site. The NMR studies also reveal the presence of a dinuclear Co(II) center in Co(II)-substituted Glx2. Steady-state and pre-steady-state kinetic studies show that Glx2 containing only 1 equiv of Zn(II) is catalytically active and that the metal ion in the consensus Zn2 site has little effect on catalytic activity. Taken together, these studies suggest that Glx2 contains a Fe(II)Zn(II) center in vivo but that the catalytic activity is due to Zn(II) in the Zn1 site

Converting GLX2-1 into an Active Glyoxalase II

Arabidopsis thaliana glyoxalase 2-1 (GLX2-1) exhibits extensive sequence similarity with GLX2 enzymes but is catalytically inactive with SLG, the GLX2 substrate. In an effort to identify residues essential for GLX2 activity, amino acid residues were altered at positions 219, 246, 248, 325, and 328 in GLX2-1 to be the same as those in catalytically active human GLX2. The resulting enzymes were overexpressed, purified, and characterized using metal analyses, fluorescence spectroscopy, and steady-state kinetics to evaluate how these residues affect metal binding, structure, and catalysis. The R246H/N248Y double mutant exhibited low level S-lactoylglutathione hydrolase activity, while the R246H/N248Y/Q325R/R328K mutant exhibited a 1.5−2-fold increase in kcat and a decrease in Km as compared to the values exhibited by the double mutant. In contrast, the R246H mutant of GLX2-1 did not exhibit glyoxalase 2 activity. Zn(II)-loaded R246H GLX2-1 enzyme bound 2 equiv of Zn(II), and 1H NMR spectra of the Co(II)-substituted analogue of this enzyme strongly suggest that the introduced histidine binds to Co(II). EPR studies indicate the presence of significant amounts a dinuclear metal ion-containing center. Therefore, an active GLX2 enzyme requires both the presence of a properly positioned metal center and significant nonmetal, enzyme−substrate contacts, with tyrosine 255 being particularly important

Report of the Pathogenesis and Pathophysiology of Lyme Disease Subcommittee of the HHS Tick Borne Disease Working Group

An understanding of the pathogenesis and pathophysiology of Lyme disease is key to the ultimate care of patients with Lyme disease. To better understand the various mechanisms underlying the infection caused by Borrelia burgdorferi, the Pathogenesis and Pathophysiology of Lyme Disease Subcommittee was formed to review what is currently known about the pathogenesis and pathophysiology of Lyme disease, from its inception, but also especially about its ability to persist in the host. To that end, the authors of this report were assembled to update our knowledge about the infectious process, identify the gaps that exist in our understanding of the process, and provide recommendations as to how to best approach solutions that could lead to a better means to manage patients with persistent Lyme disease

Divergent Evolutionary Histories of DNA Markers in a Hawaiian Population of the Coral Montipora capitata

We investigated intra- and inter-colony sequence variation in a population of the dom- inant Hawaiian coral Montipora capitata by analyzing marker gene and genomic data. Ribosomal ITS1 regions showed evidence of a reticulate history among the colonies, suggesting incomplete rDNA repeat homogenization. Analysis of the mitochondrial genome identified a major (M. capitata) and a minor (M. flabellata) haplotype in single polyp-derived sperm bundle DNA with some colonies containing 2-3 different mtDNA haplotypes. In contrast, Pax-C and newly identified single-copy nuclear genes showed either no sequence differences or minor variations in SNP frequencies segregating among the colonies. Our data suggest past mitochondrial introgression in M. capitata, whereas nuclear single-copy loci show limited variation, highlighting the divergent evolutionary histories of these coral DNA markers

Short communication: Landlab v2.0: a software package for Earth surface dynamics

umerical simulation of the form and characteristics of Earth's surface provides insight into its evolution. Landlab is an open-source Python package that contains modularized elements of numerical models for Earth's surface, thus reducing time required for researchers to create new or reimplement existing models. Landlab contains a gridding engine which represents the model domain as a dual graph of structured quadrilaterals (e.g., raster) or irregular Voronoi polygon–Delaunay triangle mesh (e.g., regular hexagons, radially symmetric meshes, and fully irregular meshes). Landlab also contains components – modular implementations of single physical processes – and a suite of utilities that support numerical methods, input/output, and visualization. This contribution describes package development since version 1.0 and backward-compatibility-breaking changes that necessitate the new major release, version 2.0. Substantial changes include refactoring the grid, improving the component standard interface, dropping Python 2 support, and creating 31 new components – for a total of 58 components in the Landlab package. We describe reasons why many changes were made in order to provide insight for designers of future packages. We conclude by discussing lessons about the dynamics of scientific software development gained from the experience of using, developing, maintaining, and teaching with Landlab