The contrasting role of heterochromatin in the differentiation of sex chromosomes: an overview from Neotropical fishes

During the evolutionary process of the sex chromosomes, a general principle that arises is that cessation or a partial restriction of recombination between the sex chromosome pair is necessary. Data from phylogenetically distinct organisms reveal that this phenomenon is frequently associated with the accumulation of heterochromatin in the sex chromosomes. Fish species emerge as excellent models to study this phenomenon because they have much younger sex chromosomes compared to higher vertebrates and many other organisms making it possible to follow their steps of differentiation. In several Neotropical fish species, the heterochromatinization, accompanied by amplification of tandem repeats, represents an important step in the morphological differentiation of simple sex chromosome systems, especially in the ZZ/ZW sex systems. In contrast, multiple sex chromosome systems have no additional increase of heterochromatin in the chromosomes. Thus, the initial stage of differentiation of the multiple sex chromosome systems seems to be associated with proper chromosomal rearrangements, whereas the simple sex chromosome systems have an accumulation of heterochromatin. In this review, attention has been drawn to this contrasting role of heterochromatin in the differentiation of simple and multiple sex chromosomes of Neotropical fishes, highlighting their surprising evolutionary dynamism.     

BaySTDetect: detecting unusual temporal patterns in small area data via Bayesian model choice

Space-time modeling of small area data is often used in epidemiology for mapping chronic disease rates and by government statistical agencies for producing local estimates of, for example, unemployment or crime rates. Although there is typically a general temporal trend, which affects all areas similarly, abrupt changes may occur in a particular area, e.g. due to emergence of localized predictors/risk factor(s) or impact of a new policy. Detection of areas with "unusual" temporal patterns is therefore important as a screening tool for further investigations. In this paper, we propose BaySTDetect, a novel detection method for short-time series of small area data using Bayesian model choice between two competing space-time models. The first model is a multiplicative decomposition of the area effect and the temporal effect, assuming one common temporal pattern across the whole study region. The second model estimates the time trends independently for each area. For each area, the posterior probability of belonging to the common trend model is calculated, which is then used to classify the local time trend as unusual or not. Crucial to any detection method, we provide a Bayesian estimate of the false discovery rate (FDR). A comprehensive simulation study has demonstrated the consistent good performance of BaySTDetect in detecting various realistic departure patterns in addition to estimating well the FDR. The proposed method is applied retrospectively to mortality data on chronic obstructive pulmonary disease (COPD) in England and Wales between 1990 and 1997 (a) to test a hypothesis that a government policy increased the diagnosis of COPD and (b) to perform surveillance. While results showed no evidence supporting the hypothesis regarding the policy, an identified unusual district (Tower Hamlets in inner London) was later recognized to have higher than national rates of hospital readmission and mortality due to COPD by the National Health Service, which initiated various local enhanced services to tackle the problem. Our method would have led to an early detection of this local health issue.     

Fruit size: Towards an understanding of the metabolic control of fruit growth using avocado as a model system

Final fruit size is the consequence of complex metabolic events that occur between fruit set and maturation. Disruption of these biochemical and molecular processes at any stage during fruit growth will impact on final fruit size. Because fruit size is a function of cell number rather than cell size, factors affecting cell division cycle activity assume importance. In this paper, we focus attention on the metabolic control of fruit growth using avocado as a model system. Three areas of current interest are highlighted, viz. the contribution by isoprenoid metabolism in the control of cell proliferation, the role played by carbohydrate content and composition in signalling changes in metabolite status and gene expression and maintenance of plant hormone homeostasis. Central to the process of fruit growth and control of final fruit size by cell division is 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) and activity of the sucrose non-fermenting 1-related protein kinase (SnRK1) complex. It is argued that sugar content and composition of sink cells impact on SnRK1 (and hexokinase) to modulate expression of sugar-metabolizing enzymes, HMGR and molybdenum cofactor (MoCo)-containing enzymes. These changes, in turn, impact on hormone metabolism by affecting allocation of the purine-derived MoCo to aldehyde oxidase and thus the endogenous concentration of indole-3-acetic acid, abscisic acid and cytokinin (CK) to alter plant hormone homeostasis. These aspects are integrated into a model to explain the metabolic control of avocado fruit growth and final fruit size.     

Tracking elusive cargo: Illuminating spatio‐temporal Type 3 effector protein dynamics using reporters

Type 3 secretion systems form an integral part of the arsenal of many pathogenic bacteria. These injection machines, together with their cargo of subversive effector proteins, are capable of manipulating the cellular environment of the host in order to ensure persistence of the pathogen. In order to fully appreciate the functions of Type 3 effectors, it is necessary to gain spatio‐temporal knowledge of each effector during the process of infection. A number of genetic modifications have been exploited in order to reveal effector protein secretion, translocation and subsequent activity, and localisation within host cells. In this review, we will discuss the many available approaches for tracking effector protein dynamics and discuss the challenges faced to improve the current technologies and gain a clearer picture of effector protein function.     

Secretion of the glucose-regulated selenoprotein SEPS1 from hepatoma cells

SEPS1 (also called selenoprotein S, SelS, Tanis or VIMP) is a selenoprotein, localized predominantly in the ER membrane and also on the cell surface. In this report, we demonstrate that SEPS1 protein is also secreted from hepatoma cells but not from five other types of cells examined. The secretion can be abolished by the ER-Golgi transport inhibitor Brefeldin A and by the protein synthesis inhibitor cycloheximide. Using a sandwich ELISA, SEPS1 was detected in the sera of 65 out of 209 human subjects (31.1%, average=15.7+/-1.1 ng/mL). Fractionation of human serum indicated that SEPS1 was associated with LDL and possibly with VLDL. The function of plasma SEPS1 is unclear but may be related to lipoprotein metabolism.     

An E. coli expression system optimized for DELLA proteins

The DELLA proteins are involved in regulation of plant growth in response to phytohormonal signals such as GA, ethylene, and auxin. They have become one of most challenging and active area of research due to their fundamental roles in plant biology. Here, we describe the first successful expression of the N-terminal domains of DELLA proteins of Arabidopsis thaliana and Malus domestica in Escherichia coli system which will be used to produce monoclonal antibodies for profiling protein micro-arrays. Optimizations of the cloning, expression, and purification using specific tags have been discussed.     

Behavior of free-ranging common dolphins (Delphinus sp.) in the Hauraki Gulf, New Zealand

Here we present the first data describing the behavior of common dolphins ( Delphinus sp.) in the Hauraki Gulf, New Zealand. Activity budgets are used to assess the effects of diel, season, depth, sea surface temperature, group size, and composition on dolphin behavior. Additionally, the presence/absence of Bryde's whale ( Balaenoptera brydei ) and Australasian gannet ( Morus serrator ) is examined in relation to dolphin behavior. Behavioral data were collected from 686 independent dolphin groups during boat-based surveys conducted between February 2002 and January 2005. Foraging (46.7%) and social (7.2%) were the most and least frequently observed behaviors, respectively. Travel (28.9%), mill (9.5%), and rest (7.7%) accounted for the remainder of the activity budget. Behavior varied seasonally, with the highest proportion of foraging and resting groups observed during the spring and autumn, respectively. Behavior also varied with water depth, with foraging animals observed in the deepest and resting groups recorded in the shallowest regions of the Hauraki Gulf. A correlation between group size and behavior was evident, although behavior did not vary with the composition of dolphin groups. Resting, milling, and socializing animals were more frequently observed in smaller group sizes. Foraging behavior was prevalent in both small and large group sizes, suggesting foraging plasticity exists within this population. Behavior differed between single- and multispecies groups, with foraging more frequent in multispecies groups. Resting, milling, or socializing was rarely observed in the presence of any associated species, indicating the primary mechanism for association is likely prey related.     

Requirements for the valid quantification of immunostains on tissue microarray materials using image analysis

Antibody‐based proteomics applied to tissue microarray (TMA) technology provides a very efficient means of visualizing and locating antigen expression in large collections of normal and pathological tissue samples. To characterize antigen expression on TMAs, the use of image analysis methods avoids the effects of human subjectivity evidenced in manual microscopical analysis. Thus, these methods have the potential to significantly enhance both precision and reproducibility. Although some commercial systems include tools for the quantitative evaluation of immunohistochemistry‐stained images, there exists no clear agreement on best practices to allow for correct and reproducible quantification results. Our study focuses on practical aspects regarding (i) image acquisition (ii) segmentation of staining and counterstaining areas and (iii) extraction of quantitative features. We illustrate our findings using a commercial system to quantify different immunohistochemistry markers targeting proteins with different expression patterns (cytoplasmic, nuclear or membranous) in colon cancer or brain tumor TMAs. Our investigations led us to identify several steps that we consider essential for standardizing computer‐assisted immunostaining quantification experiments. In addition, we propose a data normalization process based on reference materials to be able to compare measurements between studies involving different TMAs. In conclusion, we recommend certain critical prerequisites that commercial or in‐house systems should satisfy in order to permit valid immunostaining quantification.