The shape of the competition and carrying capacity kernels affects the likelihood of disruptive selection

Many quantitative genetic and adaptive dynamic models suggest that disruptive selection can maintain genetic polymorphism and be the driving force causing evolutionary divergence. These models also suggest that disruptive selection arises from frequency-dependent intraspecific competition. For convenience or historical precedence, these models assume that carrying capacity and competition functions follow a Gaussian distribution. Here, we propose a new analytical framework that relaxes the assumption of Gaussian competition and carrying capacity functions, and investigate how alternative shapes affect the likelihood of disruptive selection. We found that the shape of both carrying capacity and competition kernels interact to determine the likelihood of disruptive selection. For certain regions of the parametric space disruptive selection is facilitated, whereas for others it becomes more difficult. Our results suggest that the relationship between the degree of frequency dependence and the likelihood of disruptive selection is more complex than previously thought, depending on how resources are distributed and competition interference takes place. It is now important to describe the empirical patterns of resource distribution and competition in nature as a way to determine the likelihood of disruptive selection in natural populations.     

Isoxazole moiety in the linker region of HDAC inhibitors adjacent to the Zn-chelating group: Effects on HDAC biology and antiproliferative activity

A series of hydroxamic acid based histone deacetylase inhibitors 6–15, containing an isoxazole moiety adjacent to the Zn-chelating hydroxamic acid, is reported herein. Some of these compounds showed nanomolar activity in the HDAC isoform inhibitory assay and exhibited micro molar inhibitory activity against five pancreatic cancer cell lines.     

Commensal Bacteria Lipoteichoic Acid Increases Skin Mast Cell Antimicrobial Activity against Vaccinia Viruses

Mast cells (MCs) are considered sentinels in the skin and mucosa. Their ability to release antimicrobial peptides, such as cathelicidin, protects against bacterial infections when the epithelial barrier is breached. We recently described that MCs defend against bacterial and viral infections through the release of cathelicidin during degranulation. In this study, we hypothesize that cathelicidin expression is induced in MCs by the activation of TLR2 from bacterial products (lipoteichoic acid) produced by commensal bacteria at the epithelial surface. Our research shows that signaling through TLR2 increases the production and expression of cathelicidin in mast cells, thereby enhancing their capacity to fight vaccinia virus. MCs deficient in cathelicidin were less efficient in killing vaccinia virus after lipoteichoic acid stimulation than wild-type cells. Moreover, the activation of TLR2 increases the MC recruitment at the skin barrier interface. Taken together, our findings reveal that the expression and control of antimicrobial peptides and TLR signaling on MCs are key in fighting viral infection. Our findings also provide new insights into the pathogenesis of skin infections and suggest potential roles for MCs and TLR2 ligands in antiviral therapy.     

MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.     

A predictive aggregate transport model for microfiltration of combined macromolecular solutions and poly-disperse suspensions: testing model with transgenic goat milk

To meet the technical challenge of recovering human IgG fusion protein from transgenic whole goat milk at reasonable cost with high purity and yield, a predictive aggregate transport model for microfiltration has been developed (Baruah and Belfort, 2003). Here, to test the model's predictability of permeate flux and mass transport, a comprehensive series of experiments with varying wall shear rate, feed temperature, feed concentration, and module design are presented. A very good fit was obtained between the model predictions and measurements for a wide variety of experimental conditions. For microfiltration module design comparison, a linear hollow fiber module (representing current commercial technologies) gave lower permeation flux and higher yield than a helical hollow fiber module (representing the latest self-cleaning methodology). These results are easily explained with the model that is now being used to define operating conditions for maximizing performance. The procedure described by the model is generalizable and can be used to obtain optimal filtration performance for applications other than milk.     

Construction of a genetically modified wine yeast strain expressing the Aspergillus aculeatus rhaA gene, encoding an alpha-L-rhamnosidase of enological interest

The Aspergillus aculeatus rhaA gene encoding an alpha-L-rhamnosidase has been expressed in both laboratory and industrial wine yeast strains. Wines produced in microvinifications, conducted using a combination of the genetically modified industrial strain expressing rhaA and another strain expressing a beta-glucosidase, show increased content mainly of the aromatic compound linalool.     

Targeted elimination of peroxisome proliferator-activated receptor gamma in beta cells leads to abnormalities in islet mass without compromising glucose homeostasis

The nuclear hormone receptor peroxisome proliferator-activated receptor gamma (PPAR gamma) is an important regulator of lipid and glucose homeostasis and cellular differentiation. Studies of many cell types in vitro and in vivo have demonstrated that activation of PPAR gamma can reduce cellular proliferation. We show here that activation of PPAR gamma is sufficient to reduce the proliferation of cultured insulinoma cell lines. We created a model with mice in which the expression of the PPARG gene in beta cells was eliminated (beta gamma KO mice), and these mice were found to have significant islet hyperplasia on a chow diet. Interestingly, the normal expansion of beta-cell mass that occurs in control mice in response to high-fat feeding is markedly blunted in these animals. Despite this alteration in beta-cell mass, no effect on glucose homeostasis in beta gamma KO mice was noted. Additionally, while thiazolidinediones enhanced insulin secretion from cultured wild-type islets, administration of rosiglitazone to insulin-resistant control and beta gamma KO mice revealed that PPAR gamma in beta cells is not required for the antidiabetic actions of these compounds. These data demonstrate a critical physiological role for PPAR gamma function in beta-cell proliferation and also indicate that the mechanisms controlling beta-cell hyperplasia in obesity are different from those that regulate baseline cell mass in the islet.     

Opsin expression predicts male nuptial color in threespine stickleback

Theoretical models of sexual selection suggest that male courtship signals can evolve through the build‐up of genetic correlations between the male signal and female preference. When preference is mediated via increased sensitivity of the signal characteristics, correlations between male signal and perception/sensitivity are expected. When signal expression is limited to males, we would expect to find signal‐sensitivity correlations in males. Here, we document such a correlation within a breeding population of threespine stickleback mediated by differences in opsin expression. Males with redder nuptial coloration express more long‐wavelength‐sensitive (LWS) opsin, making them more sensitive to orange and red. This correlation is not an artifact of shared tuning to the optical microhabitat. Such correlations are an essential feature of many models of sexual selection, and our results highlight the potential importance of opsin expression variation as a substrate for signal‐preference evolution. Finally, these results suggest a potential sensory mechanism that could drive negative frequency‐dependent selection via male–male competition and thus maintain variation in male nuptial color.