Two RGS proteins that inhibit Galpha(o) and Galpha(q) signaling in C. elegans neurons require a Gbeta(5)-like subunit for function

BACKGROUND: Gbeta proteins have traditionally been thought to complex with Ggamma proteins to function as subunits of G protein heterotrimers. The divergent Gbeta(5) protein, however, can bind either Ggamma proteins or regulator of G protein signaling (RGS) proteins that contain a G gamma-like (GGL) domain. RGS proteins inhibit G protein signaling by acting as Galpha GTPase activators. While Gbeta(5) appears to bind RGS proteins in vivo, its association with Ggamma proteins in vivo has not been clearly demonstrated. It is unclear how Gbeta(5) might influence RGS activity. In C. elegans there are exactly two GGL-containing RGS proteins, EGL-10 and EAT-16, and they inhibit Galpha(o) and Galpha(q) signaling, respectively. RESULTS: We knocked out the gene encoding the C. elegans Gbeta(5) ortholog, GPB-2, to determine its physiological roles in G protein signaling. The gpb-2 mutation reduces the functions of EGL-10 and EAT-16 to levels comparable to those found in egl-10 and eat-16 null mutants. gpb-2 knockout animals are viable, and exhibit no obvious defects beyond those that can be attributed to a reduction of EGL-10 or EAT-16 function. GPB-2 protein is nearly absent in eat-16; egl-10 double mutants, and EGL-10 protein is severely diminished in gpb-2 mutants. CONCLUSIONS: Gbeta(5) functions in vivo complexed with GGL-containing RGS proteins. In the absence of Gbeta(5), these RGS proteins have little or no function. The formation of RGS-Gbeta(5) complexes is required for the expression or stability of both the RGS and Gbeta(5) proteins. Appropriate RGS-Gbeta(5) complexes regulate both Galpha(o) and Galpha(q) proteins in vivo.     

A Novel DNA Vaccine Technology Conveying Protection against a Lethal Herpes Simplex Viral Challenge in Mice

While there are a number of licensed veterinary DNA vaccines, to date, none have been licensed for use in humans. Here, we demonstrate that a novel technology designed to enhance the immunogenicity of DNA vaccines protects against lethal herpes simplex virus 2 (HSV-2) challenge in a murine model. Polynucleotides were modified by use of a codon optimization algorithm designed to enhance immune responses, and the addition of an ubiquitin-encoding sequence to target the antigen to the proteasome for processing and to enhance cytotoxic T cell responses. We show that a mixture of these codon-optimized ubiquitinated and non-ubiquitinated constructs encoding the same viral envelope protein, glycoprotein D, induced both B and T cell responses, and could protect against lethal viral challenge and reduce ganglionic latency. The optimized vaccines, subcloned into a vector suitable for use in humans, also provided a high level of protection against the establishment of ganglionic latency, an important correlate of HSV reactivation and candidate endpoint for vaccines to proceed to clinical trials.     

Morphological differences among egg nests and adult individuals of Cicadatra persica (Hemiptera,Cicadidae), distributed in Erneh,Syria

The aim of this study is determining the different patterns of egg nests and the morphological differences between the specimens of Cicadatra persica Kirkalidy, 1909 (Hemiptera: Cicadidae) distributed in fruit orchards in Erneh located on AL-Sheikh mountain south west of Syria. The appearance of 80 egg nests was studied, and the results showed that there were two basic patterns of egg nests laid by Cicadatra persica, 90% of the egg nests were of the first pattern (consists of several adjacent slits), while 10% of them were of the second pattern (consists of several divergent slits). A random sample consisting of 300 specimens (150 males and 150 females) were also studied concentrating on the differences in the color of the supra-antennal plate and in the number of spurs on the tibia of the hind legs. The results showed that there were two basic patterns of individuals based on the differences in the color of supra-antennal plate. The first pattern (individuals with yellow supra-antennal plates), constituted more than 90%, and the second one (individuals with black supra-antennal plates) constituted less than 10%. The results also showed that there were 27 different patterns based on the number of spurs on the tibia of the hind legs. One of them was a common pattern (2, 3) whose individuals have 2 spurs on the upper side of the tibia of the hind legs and 3 spurs on the lateral side of the tibia of the hind legs. The total percent of this common pattern was 76%. The other 26 patterns were different from each other, and the total percent of all these different patterns was 24%.     

Collagenase predigestion on paraffin sections enhances collagen immunohistochemical detection without distorting tissue morphology

Reliable immunohistochemical detection of collagen in formalin fixed, paraffin embedded tissues requires protease digestion. While these pan-proteases (pepsin, trypsin, protease K, etc.) enhance collagen detection, they also digest many other tissue proteins and produce poor cellular morphology and unrecognizable cellular structures. Balancing the conditions (protease type, concentration, incubation time and temperature) to digest some, but not all, proteins in a tissue section while optimizing collagen detection requires one to compromise improved collagen immunolabeling with adequate cellular morphology. Furthermore, optimal conditions for digesting tissue proteins to enhance collagen detection vary among tissue types and their fixation. Although brain is not typically subject to these deleterious consequences, structures such as epithelium, spermatids, stroma etc. and other tissues with complicated histology are profoundly affected. To resolve this technical dilemma, we discovered a novel use for collagenase to enhance collagen immunodetection without affecting the noncollagen proteins, thereby preserving tissue morphology. Collagenase, which is typically used in vitro for disassociation of cells, has never been used reliably on formalin fixed, paraffin embedded tissue sections. This new use of collagenase for immunohistochemistry promotes increased collagen immunolabeling, is easy to use, is versatile, and allows preservation of tissue structure that provides maximal and accurate histological information.     

Inference for nonlinear epidemiological models using genealogies and time series

Phylodynamics - the field aiming to quantitatively integrate the ecological and evolutionary dynamics of rapidly evolving populations like those of RNA viruses - increasingly relies upon coalescent approaches to infer past population dynamics from reconstructed genealogies. As sequence data have become more abundant, these approaches are beginning to be used on populations undergoing rapid and rather complex dynamics. In such cases, the simple demographic models that current phylodynamic methods employ can be limiting. First, these models are not ideal for yielding biological insight into the processes that drive the dynamics of the populations of interest. Second, these models differ in form from mechanistic and often stochastic population dynamic models that are currently widely used when fitting models to time series data. As such, their use does not allow for both genealogical data and time series data to be considered in tandem when conducting inference. Here, we present a flexible statistical framework for phylodynamic inference that goes beyond these current limitations. The framework we present employs a recently developed method known as particle MCMC to fit stochastic, nonlinear mechanistic models for complex population dynamics to gene genealogies and time series data in a Bayesian framework. We demonstrate our approach using a nonlinear Susceptible-Infected-Recovered (SIR) model for the transmission dynamics of an infectious disease and show through simulations that it provides accurate estimates of past disease dynamics and key epidemiological parameters from genealogies with or without accompanying time series data.     

The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis

The most salient feature of influenza evolution in humans is its antigenic drift. This process is characterized by structural changes in the virus''s B-cell epitopes and ultimately results in the ability of the virus to evade immune recognition and thereby reinfect previously infected hosts. Until recently, amino acid substitutions in epitope regions of the viral haemagglutinin were thought to be positively selected for their ability to reduce antibody binding and therefore were thought to be responsible for driving antigenic drift. However, a recent hypothesis put forward by Hensley and co-workers posits that cellular receptor binding avidity is the dominant phenotype under selection, with antigenic drift being a side effect of these binding avidity changes. Here, we present a mathematical formulation of this new antigenic drift model and use it to show how rates of antigenic drift depend on epidemiological parameters. We further use the model to evaluate how two different vaccination strategies can impact antigenic drift rates and ultimately disease incidence levels. Finally, we discuss the assumptions present in the model formulation, predictions of the model, and future work that needs to be done to determine the consistency of this hypothesis with known patterns of influenza''s genetic and antigenic evolution.     

Phylodynamic Inference and Model Assessment with Approximate Bayesian Computation: Influenza as a Case Study

A key priority in infectious disease research is to understand the ecological and evolutionary drivers of viral diseases from data on disease incidence as well as viral genetic and antigenic variation. We propose using a simulation-based, Bayesian method known as Approximate Bayesian Computation (ABC) to fit and assess phylodynamic models that simulate pathogen evolution and ecology against summaries of these data. We illustrate the versatility of the method by analyzing two spatial models describing the phylodynamics of interpandemic human influenza virus subtype A(H3N2). The first model captures antigenic drift phenomenologically with continuously waning immunity, and the second epochal evolution model describes the replacement of major, relatively long-lived antigenic clusters. Combining features of long-term surveillance data from the Netherlands with features of influenza A (H3N2) hemagglutinin gene sequences sampled in northern Europe, key phylodynamic parameters can be estimated with ABC. Goodness-of-fit analyses reveal that the irregularity in interannual incidence and H3N2''s ladder-like hemagglutinin phylogeny are quantitatively only reproduced under the epochal evolution model within a spatial context. However, the concomitant incidence dynamics result in a very large reproductive number and are not consistent with empirical estimates of H3N2''s population level attack rate. These results demonstrate that the interactions between the evolutionary and ecological processes impose multiple quantitative constraints on the phylodynamic trajectories of influenza A(H3N2), so that sequence and surveillance data can be used synergistically. ABC, one of several data synthesis approaches, can easily interface a broad class of phylodynamic models with various types of data but requires careful calibration of the summaries and tolerance parameters.