Temporal Variation in Seed Predation by Insects in a Population of Syagrus romanzoffiana (Arecaceae) in Santa Catarina Island, SC, Brazil

Insect seed predation may vary depending on seed production. The present study considers the hypothesis that the rates of seed predation tend to be smaller in years of higher fruit production. Thus, we monitored the production of fruits and predation of seeds of the palm Syagrus romanzoffiana over 2?years in the Atlantic Forest (Parque Municipal da Lagoa do Peri, Florianópolis, SC, Brazil), between July 2006 and June 2008. Plots of 0.25?m² were fitted under 20 mother plants and fruits were monthly collected for assessment of abundance and seed predation. There was variation in fruit production between the 2?years and among reproductive plants. Predation rates were high and occurred in the predispersal phase by the Curculionidae Revena rubiginosa Boheman, Anchylorhynchus aegrotus Fahraeus, and Anchylorhynchus variabilis Gyllenhal. Seed predation by these species of Anchylorhynchus is first registered in the present study. In average, about 60% of the seeds monthly produced in the population tend to escape insect predation in year of high or low production, becoming available for recruitment. The predation rate was not related to the amount of fruits produced per reproductive plant. Also, different than expected, there was a positive relation between the rates of seed predation and the total of fruits produced monthly on the plots. Thus, no evidence for the satiation of insect seed predators was found in this study with S. romanzoffiana.     

Structure-based engineering of a pectate lyase with improved specific activity for ramie degumming

Applied Microbiology and Biotechnology - Biotechnological applications of microbial pectate lyases (Pels) in plant fiber processing are promising, eco-friendly substitutes for conventional chemical...     

Probability distributed time delays: integrating spatial effects into temporal models

Background  

In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive.     

Order Reduction of the Chemical Master Equation via Balanced Realisation

We consider a Markov process in continuous time with a finite number of discrete states. The time-dependent probabilities of being in any state of the Markov chain are governed by a set of ordinary differential equations, whose dimension might be large even for trivial systems. Here, we derive a reduced ODE set that accurately approximates the probabilities of subspaces of interest with a known error bound. Our methodology is based on model reduction by balanced truncation and can be considerably more computationally efficient than solving the chemical master equation directly. We show the applicability of our method by analysing stochastic chemical reactions. First, we obtain a reduced order model for the infinitesimal generator of a Markov chain that models a reversible, monomolecular reaction. Later, we obtain a reduced order model for a catalytic conversion of substrate to a product (a so-called Michaelis-Menten mechanism), and compare its dynamics with a rapid equilibrium approximation method. For this example, we highlight the savings on the computational load obtained by means of the reduced-order model. Furthermore, we revisit the substrate catalytic conversion by obtaining a lower-order model that approximates the probability of having predefined ranges of product molecules. In such an example, we obtain an approximation of the output of a model with 5151 states by a reduced model with 16 states. Finally, we obtain a reduced-order model of the Brusselator.     

Is Bagging Effective in the Classification of Small-Sample Genomic and Proteomic Data?

There has been considerable interest recently in the application of bagging in the classification of both gene-expression data and protein-abundance mass spectrometry data. The approach is often justified by the improvement it produces on the performance of unstable, overfitting classification rules under small-sample situations. However, the question of real practical interest is whether the ensemble scheme will improve performance of those classifiers sufficiently to beat the performance of single stable, nonoverfitting classifiers, in the case of small-sample genomic and proteomic data sets. To investigate that question, we conducted a detailed empirical study, using publicly-available data sets from published genomic and proteomic studies. We observed that, under t-test and RELIEF filter-based feature selection, bagging generally does a good job of improving the performance of unstable, overfitting classifiers, such as CART decision trees and neural networks, but that improvement was not sufficient to beat the performance of single stable, nonoverfitting classifiers, such as diagonal and plain linear discriminant analysis, or 3-nearest neighbors. Furthermore, as expected, the ensemble method did not improve the performance of these classifiers significantly. Representative experimental results are presented and discussed in this work.     

Interior decoration: Tropomyosin in actin dynamics and cell migration

Cell migration and invasion requires the precise temporal and spatial orchestration of a variety of biological processes. Filaments of polymerized actin are critical players in these diverse processes, including the regulation of cell anchorage points (both cell-cell and cell-extracellular matrix), the uptake and delivery of molecules via endocytic pathways and the generation of force for both membrane protrusion and retraction. How the actin filaments are specialized for each of these discrete functions is yet to be comprehensively elucidated. The cytoskeletal tropomyosins are a family of actin associating proteins that form head-to-tail polymers which lay in the major groove of polymerized actin filaments. In the present review we summarize the emerging isoform-specific functions of tropomyosins in cell migration and invasion and discuss their potential roles in the specialization of actin filaments for the diverse cellular processes that together regulate cell migration and invasion.Key words: tropomyosin, actin, migration, invasion, cytoskeleton, actin dynamics, adhesionActin is the most abundant protein in eukaryotic cells and is critical for maintaining structural integrity. The polymerization of globular (G)-actin monomers forms actin filaments (F-actin),¹ which play a role in diverse and complex cellular functions including intercellular transport of organelles and vesicles,^2,3 cytokinesis,⁴ apoptosis⁵ and cell motility.⁶ Intricate details describing the molecular scale interactions between regulatory proteins and actin have been extensively investigated but the mechanistic control of diverse actin filament functions remain largely unclear. Recent improvements in analysis techniques⁷ and the use of physiologically relevant models of 3D cell culturing⁸ have now begun to reveal mechanisms of actin cytoskeleton regulation. Accruing evidence suggests that the actin decorating protein tropomyosin is a key regulator of actin filament specialization. Of particular interest is the impact that tropomyosin regulation has on actin filament activity during cell migration and invasion that underpins immunological cell homing, development, wound healing and metastasis.     

Exact Probability Distributions of Selected Species in Stochastic Chemical Reaction Networks

Chemical reactions are discrete, stochastic events. As such, the species’ molecular numbers can be described by an associated master equation. However, handling such an equation may become difficult due to the large size of reaction networks. A commonly used approach to forecast the behaviour of reaction networks is to perform computational simulations of such systems and analyse their outcome statistically. This approach, however, might require high computational costs to provide accurate results. In this paper we opt for an analytical approach to obtain the time-dependent solution of the Chemical Master Equation for selected species in a general reaction network. When the reaction networks are composed exclusively of zeroth and first-order reactions, this analytical approach significantly alleviates the computational burden required by simulation-based methods. By building upon these analytical solutions, we analyse a general monomolecular reaction network with an arbitrary number of species to obtain the exact marginal probability distribution for selected species. Additionally, we study two particular topologies of monomolecular reaction networks, namely (i) an unbranched chain of monomolecular reactions with and without synthesis and degradation reactions and (ii) a circular chain of monomolecular reactions. We illustrate our methodology and alternative ways to use it for non-linear systems by analysing a protein autoactivation mechanism. Later, we compare the computational load required for the implementation of our results and a pure computational approach to analyse an unbranched chain of monomolecular reactions. Finally, we study calcium ions gates in the sarco/endoplasmic reticulum mediated by ryanodine receptors.     

The Long and Viscous Road: Uncovering Nuclear Diffusion Barriers in Closed Mitosis

Diffusion barriers are effective means for constraining protein lateral exchange in cellular membranes. In Saccharomyces cerevisiae, they have been shown to sustain parental identity through asymmetric segregation of ageing factors during closed mitosis. Even though barriers have been extensively studied in the plasma membrane, their identity and organization within the nucleus remains poorly understood. Based on different lines of experimental evidence, we present a model of the composition and structural organization of a nuclear diffusion barrier during anaphase. By means of spatial stochastic simulations, we propose how specialised lipid domains, protein rings, and morphological changes of the nucleus may coordinate to restrict protein exchange between mother and daughter nuclear lobes. We explore distinct, plausible configurations of these diffusion barriers and offer testable predictions regarding their protein exclusion properties and the diffusion regimes they generate. Our model predicts that, while a specialised lipid domain and an immobile protein ring at the bud neck can compartmentalize the nucleus during early anaphase; a specialised lipid domain spanning the elongated bridge between lobes would be entirely sufficient during late anaphase. Our work shows how complex nuclear diffusion barriers in closed mitosis may arise from simple nanoscale biophysical interactions.     

Studies on the mitogenic effect of transferrin by membrane signal transduction

One of the earliest events leading to cell activation and growth is the hydrolysis of inositol phospholipids producing various membrane signals induced by an interaction between growth factors or hormones with their respective receptors on the cell membrane [1].To demonstrate the mitogenic action of transferrin,our results show that an addition of transferrin to “serum-deprived” rat hepatoma cells produced a rapid but transient rise in inositol 1,4,5-trisphosphate(IP3) level,and at the same time,an increased intracellular Ca^2 activity and a cytoplasmic alkalinization were observed.These signal transductions further lend support to the mitogenic nature of transferrin.In addition,a possible link between the receptor-mediated endocytosis of transferrin with the generation of intracellular signals is discussed herewith.