Proteome analysis of Neisseria meningitidis serogroup A

Neisseria meningitidis is an encapsulated Gram-negative bacterium responsible for significant morbidity and mortality worldwide. Meningococci are opportunistic pathogens, carried in the nasopharynx of approximately 10% of asymptomatic adults. Occasionally they enter the bloodstream to cause septicaemia and meningitis. Meningococci are classified into serogroups on the basis of polysaccharide capsule diversity, and serogroup A strains have caused major epidemics mainly in the developing world. Here we describe a two-dimensional gel electrophoresis protein map of the serogroup A strain Z4970, a clinical isolate classified as ancestral to several pandemic waves. To our knowledge this is the first systematically annotated proteomic map for N. meningitidis. Total protein samples from bacteria grown on GC-agar were electrophoretically separated and protein species were identified by matrix-assisted laser desorption/ionization time of flight spectrometry. We identified the products of 273 genes, covering several functional classes, including 94 proteins so far considered as hypothetical. We also describe several protein species encoded by genes reported by DNA microarray studies as being regulated in physiological conditions which are relevant to natural meningococcal pathogenicity. Since menA differs from other serogroups by having a fairly stable clonal population structure (i.e. with a low degree of variability), we envisaged comparative mapping as a useful tool for microevolution studies, in conjunction with established genotyping methods. As a proof of principle, we performed a comparative analysis on the B subunit of the meningococcal transferrin receptor, a vaccine candidate encoded by the tbpB gene, and a known marker of population diversity in meningococci. The results show that TbpB spot pattern variation observed in the maps of nine clinical isolates from diverse epidemic spreads, fits previous analyses based on allelic variations of the tbpB gene.     

Can cuticular lipids provide sufficient information for within-colony nepotism in wasps?

Inclusive fitness theory predicts that members of non-clonal societies will gain by directing altruistic acts towards their closest relatives. Multiple mating by queens and multiple queens creates distinct full-sister groups in many hymenopteran societies within which nepotism might occur. However, the weight of empirical data suggests that nepotism within full-sister groups is absent. It has been suggested that a lack of reliable recognition markers is responsible. In this paper, we investigated whether epicuticular lipids could provide reliable cues for intracolony kin recognition in two species of social wasps, the paper wasp Polistes dominulus and the hornet Vespa crabro. Epicuticular lipids have previously been shown to be central to kin recognition at the nest level, making them excellent candidates for within-nest discrimination. We genotyped individuals using DNA microsatellites and analysed surface chemistry by gas chromatography-mass spectrometry. We find that in both species epicuticular lipids typically could provide enough information to distinguish related nest-mates from unrelated nest-mates, a difference that occurs in colonies with multiple queens. However, in V. crabro, where colonies may be composed by different patrilines, information for discrimination between full sisters and half-sisters is weaker and prone to errors. Our data suggest that epicuticular lipids at best provide reliable information for intracolony nepotistic discrimination in multiple-queen colonies composed of unrelated lines.     

Evaluation of antioxidant effect of different extracts of Myrtus communis L

Oxidative stress is involved in the pathogenesis of numerous diseases. Nevertheless, no optimal natural antioxidant has been found for therapeutics, therefore polyphenol antioxidants have been looked for in myrtle leaves, a plant that in folk medicine has been used as anti-inflammatory drug. Antioxidant-rich fractions were prepared from myrtle (Myrtus communis L.) leaves liquid-liquid extraction (LLE) with different solvents. All myrtle extracts were very rich in polyphenols. In particular, hydroalcoholic extracts contain galloyl-glucosides, ellagitannins, galloyl-quinic acids and flavonol glycosides; ethylacetate extract and aqueous residues after LLE are enriched in flavonol glycosides and hydrolysable tannins (galloyl-glucosides, ellagitannins, galloyl-quinic acids), respectively. Qualitative and quantitative analysis for the single unidentified compound was also performed. Human LDL exposed to copper ions was used to evaluate the antioxidant activity of the myrtle extracts. Addition of these extracts did not affect the basal oxidation of LDL but dose-dependently decreased the oxidation induced by copper ions. Moreover, the myrtle extracts reduce the formation of conjugated dienes. The antioxidant effect of three myrtle extracts decreased in the following order: hydroalcoholic extracts, ethylacetate and aqueous residues after LLE. The extracts had the following IC₅₀: 0.36, 2.27 and 2.88 μM, when the sum of total phenolic compounds was considered after the correction of molecular weight based on pure compounds. Statistical analysis showed a significant difference among hydroalcoholic extracts vs. the ethylacetate and aqueous residues after LLE. These results suggest that the myrtle extracts have a potent antioxidant activity mainly due to the presence of galloyl derivatives.     

Effector role reversal during evolution: the case of frataxin in Fe-S cluster biosynthesis

Human frataxin (FXN) has been intensively studied since the discovery that the FXN gene is associated with the neurodegenerative disease Friedreich's ataxia. Human FXN is a component of the NFS1-ISD11-ISCU2-FXN (SDUF) core Fe-S assembly complex and activates the cysteine desulfurase and Fe-S cluster biosynthesis reactions. In contrast, the Escherichia coli FXN homologue CyaY inhibits Fe-S cluster biosynthesis. To resolve this discrepancy, enzyme kinetic experiments were performed for the human and E. coli systems in which analogous cysteine desulfurase, Fe-S assembly scaffold, and frataxin components were interchanged. Surprisingly, our results reveal that activation or inhibition by the frataxin homologue is determined by which cysteine desulfurase is present and not by the identity of the frataxin homologue. These data are consistent with a model in which the frataxin-less Fe-S assembly complex exists as a mixture of functional and nonfunctional states, which are stabilized by binding of frataxin homologues. Intriguingly, this appears to be an unusual example in which modifications to an enzyme during evolution inverts or reverses the mode of control imparted by a regulatory molecule.     

Morphological and thermal properties of mammalian insulation: the evolutionary transition to blubber in pinnipeds

Carnivora includes three independent evolutionary transitions to the marine environment: pinnipeds (seals, sea lions, and walruses), sea otters, and polar bears. Among these, only the pinnipeds have retained two forms of insulation, an external fur layer and an internal blubber layer for keeping warm in water. In this study we investigated key factors associated with the transition to the use of blubber, by comparing blubber characteristics among the pinnipeds. Characteristics included gross morphology (blubber thickness), fat composition (fatty acid profiles, percentage lipid, and water), and thermal conductivity. Sea lions, phocids, and walrus, which have lower fur densities than fur seals, have thicker blubber layers than fur seals (P < 0.001). Comparisons of lipid content, water content, and fatty acid composition indicated significant differences in the composition of the inner and outer regions of the blubber between groups (P < 0.001), consistent with the hypothesis that phocids and sea lions utilize the outer layer of their blubber primarily for thermal insulation, and the inner layer for energy storage. Fur seals, by contrast, rely more on their fur for thermal insulation, and utilize their blubber layer primarily for energy storage. Comparing across carnivore species, differences in total insulation (fur and/or blubber) are influenced substantially by body size and habitat, and to a lesser extent by latitudinal climate. Overall, these results indicate consistent evolutionary trends in the transition to blubber and evidence for convergent evolution of thermal traits across lineages. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ??, ??–??.     

Causality and persistence in ecological systems: a nonparametric spectral granger causality approach

Abstract Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.     

Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment

Motivation

The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the analysis. In this paper, we focus on the first two issues and assess, both on simulated (through an in silico regulation network model) and real clinical datasets, the consistency of candidate biomarkers provided by a number of different methods.

Methods

We extensively simulated the effect of heterogeneity characteristic of complex diseases on different sets of microarray data. Heterogeneity was reproduced by simulating both intrinsic variability of the population and the alteration of regulatory mechanisms. Population variability was simulated by modeling evolution of a pool of subjects; then, a subset of them underwent alterations in regulatory mechanisms so as to mimic the disease state.

Results

The simulated data allowed us to outline advantages and drawbacks of different methods across multiple studies and varying number of samples and to evaluate precision of feature selection on a benchmark with known biomarkers. Although comparable classification accuracy was reached by different methods, the use of external cross-validation loops is helpful in finding features with a higher degree of precision and stability. Application to real data confirmed these results.     

miRNAs expression analysis in paired fresh/frozen and dissected formalin fixed and paraffin embedded glioblastoma using real-time pCR

miRNAs are small molecules involved in gene regulation. Each tissue shows a characteristic miRNAs epression profile that could be altered during neoplastic transformation. Glioblastoma is the most aggressive brain tumour of the adult with a high rate of mortality. Recognizing a specific pattern of miRNAs for GBM could provide further boost for target therapy. The availability of fresh tissue for brain specimens is often limited and for this reason the possibility of starting from formalin fixed and paraffin embedded tissue (FFPE) could very helpful even in miRNAs expression analysis. We analysed a panel of 19 miRNAs in 30 paired samples starting both from FFPE and Fresh/Frozen material. Our data revealed that there is a good correlation in results obtained from FFPE in comparison with those obtained analysing miRNAs extracted from Fresh/Frozen specimen. In the few cases with a not good correlation value we noticed that the discrepancy could be due to dissection performed in FFPE samples. To the best of our knowledge this is the first paper demonstrating that the results obtained in miRNAs analysis using Real-Time PCR starting from FFPE specimens of glioblastoma are comparable with those obtained in Fresh/Frozen samples.