A bistable model of cell polarity

Ultrasensitivity, as described by Goldbeter and Koshland, has been considered for a long time as a way to realize bistable switches in biological systems. It is not as well recognized that when ultrasensitivity and reinforcing feedback loops are present in a spatially distributed system such as the cell plasmamembrane, they may induce bistability and spatial separation of the system into distinct signaling phases. Here we suggest that bistability of ultrasensitive signaling pathways in a diffusive environment provides a basic mechanism to realize cell membrane polarity. Cell membrane polarization is a fundamental process implicated in several basic biological phenomena, such as differentiation, proliferation, migration and morphogenesis of unicellular and multicellular organisms. We describe a simple, solvable model of cell membrane polarization based on the coupling of membrane diffusion with bistable enzymatic dynamics. The model can reproduce a broad range of symmetry-breaking events, such as those observed in eukaryotic directional sensing, the apico-basal polarization of epithelium cells, the polarization of budding and mating yeast, and the formation of Ras nanoclusters in several cell types.     

Bearded reedlings adjust their pair-bond behaviour in relation to the sex and attractiveness of unpaired conspecifics

An individual's investment in mating or keeping a pair bond intact may be influenced not only by the attractiveness of its current mate, but also by that of other potential mates. In this study, we investigated the effect of relative attractiveness on pair-bond behaviour in bearded reedlings, Panurus biarmicus. We showed that mate attractiveness, in terms of beard length in males and tail length in females, influenced courtship behaviour when the pair was kept isolated. In the presence of a conspecific, contact initiations within a pair increased. This increment was mainly related to the sex of the unpaired conspecific, however, and less to differences in attractiveness between the current partner and the unpaired conspecific. Female contact initiations towards potential extra mates were independent of male attractiveness, whereas male contact behaviour was significantly influenced by female attractiveness. However, females displayed more contact initiations to their current mate when they were less attractive than the unpaired females. Males decreased their overtures towards other females with increasing attractiveness of their current mates. Overall, our results suggested that, when there was a risk of losing their mate, bearded reedlings adjust their pair-bond investment mainly in response to the presence or absence of a competitor, and fine-tune investment to a lesser extent in response to the attractiveness of that potential competitor.     

Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

Background

The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover.

Methodology/Principal Findings

We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf) model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures'' representative pdf''s via the Kullback-Leibler divergence (KL). Species turnover, or diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species richness, or diversity, based on the Shannon entropy of pixel intensity.To test our approach, we specifically use the green band of Landsat images for a water conservation area in the Florida Everglades. We validate our predictions against data of species occurrences for a twenty-eight years long period for both wet and dry seasons. Our method correctly predicts 73% of species richness. For species turnover, the newly proposed KL divergence prediction performance is near 100% accurate. This represents a significant improvement over the more conventional Shannon entropy difference, which provides 85% accuracy. Furthermore, we find that changes in soil and water patterns, as measured by fluctuations of the Shannon entropy for the red and blue bands respectively, are positively correlated with changes in vegetation. The fluctuations are smaller in the wet season when compared to the dry season.

Conclusions/Significance

Texture-based statistical multiresolution image analysis is a promising method for quantifying interseasonal differences and, consequently, the degree to which vegetation, soil, and water patterns vary. The proposed automated method for quantifying species richness and turnover can also provide analysis at higher spatial and temporal resolution than is currently obtainable from expensive monitoring campaigns, thus enabling more prompt, more cost effective inference and decision making support regarding anomalous variations in biodiversity. Additionally, a matrix-based visualization of the statistical multiresolution analysis is presented to facilitate both insight and quick recognition of anomalous data.     

Kinematic and Diffusion Tensor Imaging Definition of Familial Marcus Gunn Jaw-Winking Synkinesis

Background

Marcus Gunn jaw-winking synkinesis (MGJWS) is characterized by eyelid ptosis, which disappears during jaw movement. Familial MGJWS is an extremely rare condition. Some authors suggested that MGJWS is due to neural misdirection in the brainstem whereas others suggested that aberrant reinnervation or ephapse may be responsible for synkinetic activity. Pathogenesis of this condition is therefore still unclear.

Methodology/Principal Findings

To investigate pathogenetic mechanism in familial MGJWS we performed neurophysiological (EMG, Blink Reflex, Recovery cycle of the R2 component of the blink reflex, Masseter inhibitory reflex, BAEPS and kinematic analysis) and neuroradiological (MRI, Diffusion Tensor Imaging) investigations in a member of a multigenerational family with autosomal dominant Marcus Gunn jaw-winking synkinesis (MGJWS). Kinematic analysis of eyelid and jaw movements disclosed a similar onset and offset of the eyelid and jaw in both the opening and closing phases. The excitability of brainstem circuits, as assessed by the blink reflex recovery cycle and recovery index, was normal. Diffusion Tensor Imaging revealed reduced fractional anisotropy within the midbrain tegmentum.

Conclusions/Significance

Kinematic and MRI findings point to a brainstem structural abnormality in our familial MGJWS patient thus supporting the hypothesis of a neural misdirection of trigeminal motor axons to the elevator palpebralis muscle.     

Emergence of the sudden oak death pathogen Phytophthora ramorum

The recently emerged plant pathogen Phytophthora ramorum is responsible for causing the sudden oak death epidemic. This review documents the emergence of P. ramorum based on evolutionary and population genetic analyses. Currently infection by P. ramorum occurs only in Europe and North America and three clonal lineages are distinguished: EU1, NA1 and NA2. Ancient divergence of these lineages supports a scenario in which P. ramorum originated from reproductively isolated populations and underwent at least four global migration events. This recent work sheds new light on mechanisms of emergence of exotic pathogens and provides crucial insights into migration pathways.     

Conformational selection and folding-upon-binding of intrinsically disordered protein CP12 regulate photosynthetic enzymes assembly

Carbon assimilation in plants is regulated by the reduction of specific protein disulfides by light and their re-oxidation in the dark. The redox switch CP12 is an intrinsically disordered protein that can form two disulfide bridges. In the dark oxidized CP12 forms an inactive supramolecular complex with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and phosphoribulokinase, two enzymes of the carbon assimilation cycle. Here we show that binding of CP12 to GAPDH, the first step of ternary complex formation, follows an integrated mechanism that combines conformational selection with induced folding steps. Initially, a CP12 conformation characterized by a circular structural motif including the C-terminal disulfide is selected by GAPDH. Subsequently, the induced folding of the flexible C-terminal tail of CP12 in the active site of GAPDH stabilizes the binary complex. Formation of several hydrogen bonds compensates the entropic cost of CP12 fixation and terminates the interaction mechanism that contributes to carbon assimilation control.     

An NMR-based metabolomic approach to identify the botanical origin of honey

NMR can be used in food analysis for origin discrimination and biomarker discovery using a metabolomic approach. Here, we present an example of this strategy to discriminate honey samples of different botanical origins. The NMR spectra of 353 chloroform extracts of selected honey samples were analyzed to detect possible markers of their floral origin. Six monofloral Italian honey types (acacia, linden, orange, eucalyptus, chestnut, and honeydew) were analyzed together with polyfloral samples. Specific markers were identified for each monofloral origin: two markers for acacia (chrysin and pinocembrin), one for chestnut (??-LACT-3-PKA), two for orange (8-hydroxylinalool and caffeine), one for eucalyptus (dehydrovomifoliol), one for honeydew (a diacylglycerilether) and two for linden (4-(1-hydroxy-1-methylethyl)cyclohexa-1,3-diene-carboxylic acid and 4-(1-methylethenyl)cyclohexa-1,3-diene-carboxylic acid). An NMR-based metabolomic approach that used O2PLS-DA multivariate data analysis allowed us to discriminate the different types of honey. Two different classifiers were built based on different multivariate techniques. The high precision of the classification obtained suggests that this approach could be useful to develop generally applicable metabolomic tools to discriminate the origin of honey samples.