Magnetosheath High-Speed Jets: Internal Structure and InteractionWith Ambient Plasma

National Aeronautics and Space Administration (NASA). Grant Number: NNG04EB99C; Österreichische Forschungsförderungsgesellschaft (FFG); Austrian Academy of Sciences and the Austrian Space Applications Programme. Grant Number: FFG/ASAP-844377; NASA. Grant Numbers: NNX17AI45G, NAS5-02099; Austrian Science Fund (FWF). Grant Number: P 28764-N2

Development of a Low Bias Method for Characterizing Viral Populations Using Next Generation Sequencing Technology

Background: With an estimated 38 million people worldwide currently infected with human immunodeficiency virus (HIV), and an additional 4.1 million people becoming infected each year, it is important to understand how this virus mutates and develops resistance in order to design successful therapies. Methodology/Principal Findings: We report a novel experimental method for amplifying full-length HIV genomes without the use of sequence-specific primers for high throughput DNA sequencing, followed by assembly of full length viral genome sequences from the resulting large dataset. Illumina was chosen for sequencing due to its ability to provide greater coverage of the HIV genome compared to prior methods, allowing for more comprehensive characterization of the heterogeneity present in the HIV samples analyzed. Our novel amplification method in combination with Illumina sequencing was used to analyze two HIV populations: a homogenous HIV population based on the canonical NL4-3 strain and a heterogeneous viral population obtained from a HIV patient's infected T cells. In addition, the resulting sequence was analyzed using a new computational approach to obtain a consensus sequence and several metrics of diversity. Significance: This study demonstrates how a lower bias amplification method in combination with next generation DNA sequencing provides in-depth, complete coverage of the HIV genome, enabling a stronger characterization of the quasispecies present in a clinically relevant HIV population as well as future study of how HIV mutates in response to a selective pressure

A Two-Hybrid Assay to Study Protein Interactions within the Secretory Pathway

Interactions of transcriptional activators are difficult to study using transcription-based two-hybrid assays due to potent activation resulting in false positives. Here we report the development of the Golgi two-hybrid (G2H), a method that interrogates protein interactions within the Golgi, where transcriptional activators can be assayed with negligible background. The G2H relies on cell surface glycosylation to report extracellularly on protein-protein interactions occurring within the secretory pathway. In the G2H, protein pairs are fused to modular domains of the reporter glycosyltransferase, Och1p, and proper cell wall formation due to Och1p activity is observed only when a pair of proteins interacts. Cells containing interacting protein pairs are identified by selectable phenotypes associated with Och1p activity and proper cell wall formation: cells that have interacting proteins grow under selective conditions and display weak wheat germ agglutinin (WGA) binding by flow cytometry, whereas cells that lack interacting proteins display stunted growth and strong WGA binding. Using this assay, we detected the interaction between transcription factor MyoD and its binding partner Id2. Interfering mutations along the MyoD:Id2 interaction interface ablated signal in the G2H assay. Furthermore, we used the G2H to detect interactions of the activation domain of Gal4p with a variety of binding partners. Finally, selective conditions were used to enrich for cells encoding interacting partners. The G2H detects protein-protein interactions that cannot be identified via traditional two-hybrid methods and should be broadly useful for probing previously inaccessible subsets of the interactome, including transcriptional activators and proteins that traffic through the secretory pathway

Entropy-driven liquid-liquid separation in supercooled water

Twenty years ago Poole et al. (Nature 360, 324, 1992) suggested that the anomalous properties of supercooled water may be caused by a critical point that terminates a line of liquid-liquid separation of lower-density and higher-density water. Here we present an explicit thermodynamic model based on this hypothesis, which describes all available experimental data for supercooled water with better quality and with fewer adjustable parameters than any other model suggested so far. Liquid water at low temperatures is viewed as an 'athermal solution' of two molecular structures with different entropies and densities. Alternatively to popular models for water, in which the liquid-liquid separation is driven by energy, the phase separation in the athermal two-state water is driven by entropy upon increasing the pressure, while the critical temperature is defined by the 'reaction' equilibrium constant. In particular, the model predicts the location of density maxima at the locus of a near-constant fraction (about 0.12) of the lower-density structure.Comment: 7 pages, 6 figures. Version 2 contains an additional supplement with tables for the mean-field equatio

RT-qPCR reveals opsin gene upregulation associated with age and sex in guppies (Poecilia reticulata) - a species with color-based sexual selection and 11 visual-opsin genes

<p>Abstract</p> <p>Background</p> <p>PCR-based surveys have shown that guppies (<it>Poecilia reticulata</it>) have an unusually large visual-opsin gene repertoire. This has led to speculation that opsin duplication and divergence has enhanced the evolution of elaborate male coloration because it improves spectral sensitivity and/or discrimination in females. However, this conjecture on evolutionary connections between opsin repertoire, vision, mate choice, and male coloration was generated with little data on gene expression. Here, we used RT-qPCR to survey visual-opsin gene expression in the eyes of males, females, and juveniles in order to further understand color-based sexual selection from the perspective of the visual system.</p> <p>Results</p> <p>Juvenile and adult (male and female) guppies express 10 visual opsins at varying levels in the eye. Two opsin genes in juveniles, <it>SWS2B </it>and <it>RH2-2</it>, accounted for >85% of all visual-opsin transcripts in the eye, excluding <it>RH1</it>. This relative abundance (RA) value dropped to about 65% in adults, as <it>LWS-A180 </it>expression increased from approximately 3% to 20% RA. The juvenile-to-female transition also showed <it>LWS-S180 </it>upregulation from about 1.5% to 7% RA. Finally, we found that expression in guppies' <it>SWS2-LWS </it>gene cluster is negatively correlated with distance from a candidate locus control region (LCR).</p> <p>Conclusions</p> <p>Selective pressures influencing visual-opsin gene expression appear to differ among age and sex. <it>LWS </it>upregulation in females is implicated in augmenting spectral discrimination of male coloration and courtship displays. In males, enhanced discrimination of carotenoid-rich food and possibly rival males are strong candidate selective pressures driving <it>LWS </it>upregulation. These developmental changes in expression suggest that adults possess better wavelength discrimination than juveniles. Opsin expression within the <it>SWS2-LWS </it>gene cluster appears to be regulated, in part, by a common LCR. Finally, by comparing our RT-qPCR data to MSP data, we were able to propose the first opsin-to-λ_maxassignments for all photoreceptor types in the cone mosaic.</p

Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models

Genome-scale network reconstructions are useful tools for understanding cellular metabolism, and comparisons of such reconstructions can provide insight into metabolic differences between organisms. Recent efforts toward comparing genome-scale models have focused primarily on aligning metabolic networks at the reaction level and then looking at differences and similarities in reaction and gene content. However, these reaction comparison approaches are time-consuming and do not identify the effect network differences have on the functional states of the network. We have developed a bilevel mixed-integer programming approach, CONGA, to identify functional differences between metabolic networks by comparing network reconstructions aligned at the gene level. We first identify orthologous genes across two reconstructions and then use CONGA to identify conditions under which differences in gene content give rise to differences in metabolic capabilities. By seeking genes whose deletion in one or both models disproportionately changes flux through a selected reaction (e.g., growth or by-product secretion) in one model over another, we are able to identify structural metabolic network differences enabling unique metabolic capabilities. Using CONGA, we explore functional differences between two metabolic reconstructions of Escherichia coli and identify a set of reactions responsible for chemical production differences between the two models. We also use this approach to aid in the development of a genome-scale model of Synechococcus sp. PCC 7002. Finally, we propose potential antimicrobial targets in Mycobacterium tuberculosis and Staphylococcus aureus based on differences in their metabolic capabilities. Through these examples, we demonstrate that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of metabolic models at a functional level. Using CONGA, we can identify differences in reaction and gene content which give rise to different functional predictions. Because CONGA provides a general framework, it can be applied to find functional differences across models and biological systems beyond those presented here

Type IV Secretion-Dependent Activation of Host MAP Kinases Induces an Increased Proinflammatory Cytokine Response to Legionella pneumophila

The immune system must discriminate between pathogenic and nonpathogenic microbes in order to initiate an appropriate response. Toll-like receptors (TLRs) detect microbial components common to both pathogenic and nonpathogenic bacteria, whereas Nod-like receptors (NLRs) sense microbial components introduced into the host cytosol by the specialized secretion systems or pore-forming toxins of bacterial pathogens. The host signaling pathways that respond to bacterial secretion systems remain poorly understood. Infection with the pathogen Legionella pneumophila, which utilizes a type IV secretion system (T4SS), induced an increased proinflammatory cytokine response compared to avirulent bacteria in which the T4SS was inactivated. This enhanced response involved NF-κB activation by TLR signaling as well as Nod1 and Nod2 detection of type IV secretion. Furthermore, a TLR- and RIP2-independent pathway leading to p38 and SAPK/JNK MAPK activation was found to play an equally important role in the host response to virulent L. pneumophila. Activation of this MAPK pathway was T4SS-dependent and coordinated with TLR signaling to mount a robust proinflammatory cytokine response to virulent L. pneumophila. These findings define a previously uncharacterized host response to bacterial type IV secretion that activates MAPK signaling and demonstrate that coincident detection of multiple bacterial components enables immune discrimination between virulent and avirulent bacteria