Reduced production of superoxide (02(-)] in peritoneal macrophages of the rat submitted to acute alcoholic intoxication

Acute ethanol administration by intragastric tube caused an impairment of the superoxide anion production by rat peritoneal macrophages as compared to controls. Since the oxidative-dependent microbicidal system plays a crucial role, at cellular level, in the host defence mechanisms, this work may explain, at last in part, the reduced resistence of alcoholics to infections.     

Glutamate triggers intracellular Ca2+ oscillations and nitric oxide release by inducing NAADP- and InsP3-dependent Ca2+ release in mouse brain endothelial cells

The neurotransmitter glutamate increases cerebral blood flow by activating postsynaptic neurons and presynaptic glial cells within the neurovascular unit. Glutamate does so by causing an increase in intracellular Ca²⁺ concentration ([Ca²⁺]_i) in the target cells, which activates the Ca²⁺/Calmodulin-dependent nitric oxide (NO) synthase to release NO. It is unclear whether brain endothelial cells also sense glutamate through an elevation in [Ca²⁺]_i and NO production. The current study assessed whether and how glutamate drives Ca²⁺-dependent NO release in bEND5 cells, an established model of brain endothelial cells. We found that glutamate induced a dose-dependent oscillatory increase in [Ca²⁺]_i, which was maximally activated at 200 μM and inhibited by α-methyl-4-carboxyphenylglycine, a selective blocker of Group 1 metabotropic glutamate receptors. Glutamate-induced intracellular Ca²⁺ oscillations were triggered by rhythmic endogenous Ca²⁺ mobilization and maintained over time by extracellular Ca²⁺ entry. Pharmacological manipulation revealed that glutamate-induced endogenous Ca²⁺ release was mediated by InsP₃-sensitive receptors and nicotinic acid adenine dinucleotide phosphate (NAADP) gated two-pore channel 1. Constitutive store-operated Ca²⁺ entry mediated Ca²⁺ entry during ongoing Ca²⁺ oscillations. Finally, glutamate evoked a robust, although delayed increase in NO levels, which was blocked by pharmacologically inhibition of the accompanying intracellular Ca²⁺ signals. Of note, glutamate induced Ca²⁺-dependent NO release also in hCMEC/D3 cells, an established model of human brain microvascular endothelial cells. This investigation demonstrates for the first time that metabotropic glutamate-induced intracellular Ca²⁺ oscillations and NO release have the potential to impact on neurovascular coupling in the brain.     

Trophic ecology of northern Australia's terapontids: ontogenetic dietary shifts and feeding classification

The diets of 21 terapontid species from freshwater environments in northern Australia were investigated to determine the similarity and dissimilarity among species and the extent of any ontogenetic shifts. Distinct ontogenetic dietary shifts occurred in all species for which sufficient data were available, with many species passing through several discrete trophic categories during their life histories. Diets of all juvenile terapontids were similar, mainly comprising aquatic insects and zooplankton. Larger size classes of terapontids diverged into a broad spectrum of feeding groups comprising carnivorous dietary modes (including piscivory and lepidophagy), omnivory (including frugivory and consumption of allochthonous prey), herbivory and detritivory. The results indicate that the terapontids represent Australia's most trophically diverse freshwater fish family.     

Multi-scale inference of interaction rules in animal groups using Bayesian model selection

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis). We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.     

Scale-independent roughness value of cell membranes studied by means of AFM technique

The roughness of cell membrane is a very interesting indicator of cell's health state. Atomic Force Microscopy allows us to investigate the roughness of cell membrane in great detail, but the obtained roughness value is scale-dependent, i.e. it strongly depends on measurement parameters, as scanning area and step size. The scale-dependence of the roughness value can be reduced by means of data filtration techniques, that are not standardized at nanometric scale, especially as far as biological data are concerned. In this work, a new method, based on the changes of values of some roughness parameter (root mean square roughness and skewness) as a function of filtration frequencies, has been implemented to optimize data filtering procedure in the calculation of cell membrane roughness. In this way, a root mean square roughness value independent of cell shape, membrane micro-irregularities and measurement parameters can be obtained. Moreover, different filtration frequencies selected with this method allow us to discriminate different surface regimes (nominal form, waviness and roughness) belonging to the raw cell profile, each one related to different features of the cell surface.     

progressiveMauve: Multiple Genome Alignment with Gene Gain,Loss and Rearrangement

Background

Multiple genome alignment remains a challenging problem. Effects of recombination including rearrangement, segmental duplication, gain, and loss can create a mosaic pattern of homology even among closely related organisms.

Methodology/Principal Findings

We describe a new method to align two or more genomes that have undergone rearrangements due to recombination and substantial amounts of segmental gain and loss (flux). We demonstrate that the new method can accurately align regions conserved in some, but not all, of the genomes, an important case not handled by our previous work. The method uses a novel alignment objective score called a sum-of-pairs breakpoint score, which facilitates accurate detection of rearrangement breakpoints when genomes have unequal gene content. We also apply a probabilistic alignment filtering method to remove erroneous alignments of unrelated sequences, which are commonly observed in other genome alignment methods. We describe new metrics for quantifying genome alignment accuracy which measure the quality of rearrangement breakpoint predictions and indel predictions. The new genome alignment algorithm demonstrates high accuracy in situations where genomes have undergone biologically feasible amounts of genome rearrangement, segmental gain and loss. We apply the new algorithm to a set of 23 genomes from the genera Escherichia, Shigella, and Salmonella. Analysis of whole-genome multiple alignments allows us to extend the previously defined concepts of core- and pan-genomes to include not only annotated genes, but also non-coding regions with potential regulatory roles. The 23 enterobacteria have an estimated core-genome of 2.46Mbp conserved among all taxa and a pan-genome of 15.2Mbp. We document substantial population-level variability among these organisms driven by segmental gain and loss. Interestingly, much variability lies in intergenic regions, suggesting that the Enterobacteriacae may exhibit regulatory divergence.

Conclusions

The multiple genome alignments generated by our software provide a platform for comparative genomic and population genomic studies. Free, open-source software implementing the described genome alignment approach is available from http://gel.ahabs.wisc.edu/mauve.