Effect of adenovirus and influenza virus infection on obesity

The purpose of this review is to provide an overview of the effects of adenovirus and influenza virus infections on obesity in various experimental models. We reviewed studies that were conducted within the past 10 years and were related to virus infection and obesity prevalence. Here, we discuss a different causal relationship between adenovirus and influenza infections with obesity. Adenovirus infection can cause obesity, whereas obesity can be a risk factor for increasing influenza virus infection and increases the risk of morbidity and mortality. The prevalence of obesity due to adenovirus infections may be due to an increase in glucose uptake and reduction in lipolysis caused by an increase in corticosterone secretion. Adenovirus infections may lead to increases in appetite by decreasing norepinephrine and leptin levels and also cause immune dysfunction. The relationship between obesity and influenza virus infection could be summarized by the following features: decreases in memory T-cell functionality and interferon (IFN)-α, IFN-β, and IFN-γ mRNA expression, increases in viral titer and infiltration, and impaired dendritic cell function in obese individuals. Moreover, leptin resistance may play an important role in increasing influenza virus infections in obese individuals. In conclusion, prevention of adenovirus infections could be a good approach for reducing obesity prevalence, and prevention of obesity could reduce influenza virus infections from the point of view of viral infections and obesity.     

Isolation and functional analysis of a 24-residue linear alpha-helical antimicrobial peptide from Korean blackish cicada, Cryptotympana dubia (Homoptera)

A new antimicrobial peptide, cryptonin, was isolated and characterized from the adult Korean blackish cicada, Cryptotympana dubia. It consists of 24 amino acid residues and has a molecular weight of 2,704 Da on mass spectroscopy. The predicted alpha-helical structure analysis and increased helix percent in 40% trifloroethanol of cryptonin suggests that it belongs to the typical linear alpha-helix forming peptide. Binding of the biotin-labeled cryptonin at the surface of E. coli cells and increased influx of propidium iodide in E. coli after cryptonin treatment indicates that it kills microbial cells by binding bacterial cell surfaces and disrupting the cell permeability. Cryptonin showed strong antibacterial (MIC 1.56-25 microg/ml) and antifungal (MIC 3.12-50 microg/ml) activities against tested bacteria and fungi including two antibiotic-resistant bacterial strains; methicilin-resistant S. aureus and vancomycin-resistant Enterococci (MIC 25 microg/ml, each).     

Identification of an intronic splicing regulatory element involved in auto‐regulation of alternative splicing of SCL33 pre‐mRNA

In Arabidopsis, pre‐mRNAs of serine/arginine‐rich (SR) proteins undergo extensive alternative splicing (AS). However, little is known about the cis‐elements and trans‐acting proteins involved in regulating AS. Using a splicing reporter (GFP–intron–GFP), consisting of the GFP coding sequence interrupted by an alternatively spliced intron of SCL33, we investigated whether cis‐elements within this intron are sufficient for AS, and which SR proteins are necessary for regulated AS. Expression of the splicing reporter in protoplasts faithfully produced all splice variants from the intron, suggesting that cis‐elements required for AS reside within the intron. To determine which SR proteins are responsible for AS, the splicing pattern of the GFP–intron–GFP reporter was investigated in protoplasts of three single and three double mutants of SR genes. These analyses revealed that SCL33 and a closely related paralog, SCL30a, are functionally redundant in generating specific splice variants from this intron. Furthermore, SCL33 protein bound to a conserved sequence in this intron, indicating auto‐regulation of AS. Mutations in four GAAG repeats within the conserved region impaired generation of the same splice variants that are affected in the scl33 scl30a double mutant. In conclusion, we have identified the first intronic cis‐element involved in AS of a plant SR gene, and elucidated a mechanism for auto‐regulation of AS of this intron.     

Model-Based Simulation and Prediction of an Antiviral Strategy against Influenza A Infection

There is a strong need to develop novel strategies in using antiviral agents to efficiently treat influenza infections. Thus, we constructed a rule-based mathematical model that reflects the complicated interactions of the host immunity and viral life cycle and analyzed the key controlling steps of influenza infections. The main characteristics of the pandemic and seasonal influenza strains were estimated using parameter values derived from cells infected with Influenza A/California/04/2009 and Influenza A/NewCaledonia/20/99, respectively. The quantitative dynamics of the infected host cells revealed a more aggressive progression of the pandemic strain than the seasonal strain. The perturbation of each parameter in the model was then tested for its effects on viral production. In both the seasonal and pandemic strains, the inhibition of the viral release (k_C), the reinforcement of viral attachment (k_V), and an increased transition rate of infected cells into activated cells (k_I) exhibited significant suppression effects on the viral production; however, these inhibitory effects were only observed when the numerical perturbations were performed at the early stages of the infection. In contrast, combinatorial perturbations of both the inhibition of viral release and either the reinforcement of the activation of infected cells or the viral attachment exhibited a significant reduction in the viral production even at a later stage of infection. These results suggest that, in addition to blocking the viral release, a combination therapy that also enhances either the viral attachment or the transition of the infected cells might provide an alternative for effectively controlling progressed influenza infection.     

Slit2 Inactivates GSK3β to Signal Neurite Outgrowth Inhibition

Slit molecules comprise one of the four canonical families of axon guidance cues that steer the growth cone in the developing nervous system. Apart from their role in axon pathfinding, emerging lines of evidence suggest that a wide range of cellular processes are regulated by Slit, ranging from branch formation and fasciculation during neurite outgrowth to tumor progression and to angiogenesis. However, the molecular and cellular mechanisms downstream of Slit remain largely unknown, in part, because of a lack of a readily manipulatable system that produces easily identifiable traits in response to Slit. The present study demonstrates the feasibility of using the cell line CAD as an assay system to dissect the signaling pathways triggered by Slit. Here, we show that CAD cells express receptors for Slit (Robo1 and Robo2) and that CAD cells respond to nanomolar concentrations of Slit2 by markedly decelerating the rate of process extension. Using this system, we reveal that Slit2 inactivates GSK3β and that inhibition of GSK3β is required for Slit2 to inhibit process outgrowth. Furthermore, we show that Slit2 induces GSK3β phosphorylation and inhibits neurite outgrowth in adult dorsal root ganglion neurons, validating Slit2 signaling in primary neurons. Given that CAD cells can be conveniently manipulated using standard molecular biological methods and that the process extension phenotype regulated by Slit2 can be readily traced and quantified, the use of a cell line CAD will facilitate the identification of downstream effectors and elucidation of signaling cascade triggered by Slit.     

Heterogeneity–diversity relationships in sessile organisms: a unified framework

The hypothesis that environmental heterogeneity promotes species richness by increasing opportunities for niche partitioning is a fundamental paradigm in ecology. However, recent studies suggest that heterogeneity–diversity relationships (HDR) are more complex than expected from this niche‐based perspective, and often show a decrease in richness at high levels of heterogeneity. These findings have motivated ecologists to propose new mechanisms that may explain such deviations. Here we provide an overview of currently recognised mechanisms affecting the shape of HDRs and present a conceptual model that integrates all previously proposed mechanisms within a unified framework. We also translate the proposed framework into an explicit community dynamic model and use the model as a tool for generating testable predictions concerning how landscape properties interact with species traits in determining the shape of HDRs. Our main finding is that, despite the enormous complexity of such interactions, the predicted HDRs are rather simple, ranging from positive to unimodal patterns in a highly consistent and predictable manner.