A Multiscale Hybrid Model for Pro-angiogenic Calcium Signals in a Vascular Endothelial Cell

Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions. Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progression.     

Extracellular cysteines define ectopeptidase (APN, CD13) expression and function

Alanyl aminopeptidase (APN) is a surface-bound metallopeptidase that processes the N-terminals of biologically active peptides such as enkephalins, angiotensins, neurokinins, and cytokines. It exerts profound activity on vital processes such as immune response, cellular growth, and blood pressure control. Inhibition of either APN gene expression or its enzymatic activity severely affects leukocyte growth and function. We show here that oxidoreductase-mediated modulations of the cell surface thiol status affect the enzymatic activity of APN. Additional evidence for the pivotal role of extracellular cysteines in the APN molecule was obtained when substitution of any of these six cysteines caused complete loss of surface expression and enzymatic activity. In contrast, the transmembrane Cys24 appears to have no similar function. Enzymatically inactive cysteine mutants were retained in the endoplasmic reticulum as shown by high-resolution imaging and Endoglycosidase H digestion. In the absence of any crystal-structure data, the demonstration that individual extracellular cysteines contribute to APN expression and function appears to be of particular importance. The data are the first to show thiol-dependent modulation of the activity of a typical surface-bound peptidase at the cell surface, probably reflecting a general regulating mechanism. This may relate to various disease processes such as inflammation or malignant transformation.     

A novel spirocyclic tropanyl-Δ2-isoxazoline derivative enhances citalopram and paroxetine binding to serotonin transporters as well as serotonin uptake

A group of spirocyclic tropanyl-Δ²-isoxazolines was synthesized exploiting the 1,3-dipolar cycloaddition of nitrile oxides to olefins. Their interaction with the dopamine and serotonin transporters (DAT and SERT, respectively) was evaluated through binding experiments. The majority of the compounds had no inhibitory effects (IC₅₀ >> 10 μM), while some had an IC₅₀ value in the range 5–10 μM (8a–c, 10b and 11c on DAT, 12b on SERT). Unexpectedly, one of the tertiary amines under investigation, that is 3′-methoxy-8-methyl-spiro{8-azabicyclo[3.2.1]octane-3,5′(4′H)-isoxazole 7a, was able to enhance at a concentration of 10 μM both [³H]citalopram and [³H]paroxetine binding to SERT in rat brain homogenate (up to 25%, due to an increase of B_max) and [³H]serotonin uptake (up to 30%) in cortical synaptosomes. This peculiar pharmacological profile of 7a suggests it binds to an allosteric site on SERT, and positions derivative 7a as a very useful tool to investigate SERT machinery.     

SNUFER: A software for localization and presentation of single nucleotide polymorphisms using a Clustal multiple sequence alignment output file

SNUFER is a software for the automatic localization and generation of tables used for the presentation of single nucleotide polymorphisms (SNPs). After input of a fasta file containing the sequences to be analyzed, a multiple sequence alignment is generated using ClustalW ran inside SNUFER. The ClustalW output file is then used to generate a table which displays the SNPs detected in the aligned sequences and their degree of similarity. This table can be exported to Microsoft Word, Microsoft Excel or as a single text file, permitting further editing for publication. The software was written using Delphi 7 for programming and FireBird 2.0 for sequence database management. It is freely available for noncommercial use and can be downloaded from http://www.heranza.com.br/bioinformatica2.htm.     

Cryptococcus neoformans var. grubii - Pathogenicity of environmental isolates correlated to virulence factors, susceptibility to fluconazole and molecular profile

The pathogenicity of Cryptococcus neoformans is heterogeneous and is associated with the expression of virulence factors. This study aimed to correlate the pathogenicity of C. neoformans var. grubii in BALB/c mice with in vitro virulence factors, fluconazole minimal inhibitory concentrations (MICs) and molecular profiles, before and after animal passage. Ten environmental isolates and one ATCC strain of C. neoformans var. grubii mating type α were evaluated. Most isolates (91%) killed 50% or more of the infected animals by day 24 postinfection and were recovered from the lungs and brains of surviving animals on days 7 and 14 postinfection. The burden of yeast in the lungs was more variable than that in the brain. The differences in the expression of virulence factors (growth at 37oC, presence and size of the capsule and production of melanin, urease, proteinase and phospholipase) by most isolates pre and postpassage in animals were not statistically significant. The fluconazole MICs in postpassaged lines differed by a one-dilution from the MIC of the corresponding prepassaged line for six isolates. Using molecular typing [polymerase chain reaction-fingerprinting with (GACA)4 and M13], eight isolates were identified as VNI and three as VNII. We concluded that different isolates with the same molecular and phenotypic profiles, including isolates that are markedly hypervirulent, span a wide range of virulence and there were no changes in virulence factors in the postpassaged lines when compared with the corresponding nonpassaged lines.     

Assessing the functional turnover of species assemblages with tailored dissimilarity matrices

It is often suggested that community functional diversity is an appropriate predictive measure of ecosystem functioning, particularly if relevant species traits for the ecological property of interest are carefully selected. However, methods for selecting traits are often based on expert knowledge or on theoretical models of ecosystem functioning, but usually do not include explicitly developed quantitative procedures. Here we propose to construct a so‐called ‘tailored dissimilarity matrix’ between species assemblages to emphasize their functional turnover in response to some user‐defined ecological property. First, a subset of community weighted mean trait values (CWM) is selected by stepwise regression on the ecological process of interest. The selected CWM values are then replaced by the residuals of the least‐squares regressions of each single CWM on the ecological process of interest and pairwise Euclidean distances between the residual values at each sampling site are calculated. We illustrate the advantages of the tailored approach using two distinct plant and bee communities under contrasting fire regimes in temperate forests of southern Switzerland. Our results demonstrated that, unlike for the original CWM values, the tailored approach optimized the degree of functional differentiation among bee and plant species assemblages, i.e. the species functional turnover, with respect to different fire regimes.     

Key parameters for outdoor biomass production of Scenedesmus obliquus in solar tracked photobioreactors

The biomass productivity of Scenedesmus obliquus was investigated outdoors during all seasons in solar tracked flat panel photobioreactors (PBR) to evaluate key parameters for process optimization. CO₂ was supplied by flue gas from an attached combined block heat and power plant. Waste heat from the power plant was used to heat the culture during winter. The parameters pH, CO₂, and inorganic salt concentrations were automatically adjusted to nonlimiting levels. The optimum biomass concentration increased directly with the photosynthetic active radiation (PAR) from 3 to 5 g dry weight (DW)?L^?1 for a low PAR of 10 mol photons m^?2 day^?1 and high PAR of 40–60 mol photons m^?2 day^?1, respectively. The annual average biomass yield (photosynthetic efficiency) was 0.4?±?0.5 g DW mol^?1 photons. However, biomass yields of 1.5 g DW mol^?1 photons close to the theoretical maximum were obtained at low PAR. The productivity (including the night biomass losses) ranged during all seasons from ?5 up to 30 g DW m^?2 day^?1 with a mean productivity of 9?±?7 g DW m^?2 day^?1. Low night temperatures of the culture medium and elevated day temperatures to the species-specific optimum increased the productivity. Thus, continuous regulation of the biomass concentration and the culture temperature with regard to the fluctuating weather conditions is essential for process optimization of outdoor microalgal production systems in temperate climates.     

Synthesis, pharmacological evaluation, and structure-activity relationships of benzopyran derivatives with potent SERM activity

The synthesis, binding affinity for estrogen receptor subtypes (ER alpha and ER beta) and pharmacological activity on rat uterus of a new class of potent ligands, characterized by a 3-phenylbenzopyran scaffold with a basic side chain in position 4, are reported. Some of these compounds, endowed with very high receptor affinity, showed potent inhibition of agonist-stimulated uterine growth, with no or limited proliferative effect. Binding affinity mostly depended on the nature and position of substituents at the 3-phenyl ring, while the uterine activity seems to be affected by basic chain length. Compound 9c (CHF4227) showed excellent binding affinity and antagonist activity on the uterus. The docking of benzopyran derivatives explained the structure-affinity relationships observed for 3-phenyl substitution: a small, hydrophobic 4'-substituent could interact with a small accessory binding cavity, while di-substitution at 4' and 3' led to some ER alpha selectivity. This selectivity can be ascribed to differences in amino acid composition and side chain conformation in the region accommodating the 3-phenyl ring at human ER alpha and ER beta ligand-binding domain.     

Barley Mla and Rar mutants compromised in the hypersensitive cell death response against Blumeria graminis f.sp. hordei are modified in their ability to accumulate reactive oxygen intermediates at sites of fungal invasion

 The pathogenesis-related accumulation of superoxide radical anions (O^·− ₂) and hydrogen peroxide (H₂O₂) was comparatively analyzed in a barley line (Hordeum vulgare L. cv Sultan-5) carrying the powdery mildew (Blumeria graminis f.sp. hordei, Speer, Bgh) resistance gene Mla12, and in susceptible mutants defective in Mla12 or in genes “required for Mla12-specified disease resistance” (Rar1 and Rar2). In-situ localization of reactive oxygen intermediates was performed both by microscopic detection of azide-insensitive nitroblue tetrazolium (NBT) reduction or diaminobenzidine (DAB) polymerization, and by an NBT-DAB double-staining procedure. The Mla12-mediated hypersensitive cell death occurred either in attacked epidermal cells or adjacent mesophyll cells of wild-type plants. Whole-cell H₂O₂ accumulation was detected in dying cells, while O^·− ₂ emerged in adjacent cells. Importantly, all susceptible mutants lacked these reactions. An oxalate oxidase, which is known to generate H₂O₂ and has been implicated in barley resistance against the powdery mildew fungus, was not differentially expressed between the wild type and all mutants. The results demonstrate that the Rar1 and Rar2 gene products, which are control elements of R-gene-mediated programmed cell death, also control accumulation of reactive oxygen intermediates but not the pathogenesis-related expression of oxalate oxidase. Received: 7 January 2000 / Accepted: 2 June 2000     

Bayesian Markov Random Field Analysis for Protein Function Prediction Based on Network Data

Inference of protein functions is one of the most important aims of modernbiology. To fully exploit the large volumes of genomic data typically producedin modern-day genomic experiments, automated computational methods for proteinfunction prediction are urgently needed. Established methods use sequence orstructure similarity to infer functions but those types of data do not sufficeto determine the biological context in which proteins act. Currenthigh-throughput biological experiments produce large amounts of data on theinteractions between proteins. Such data can be used to infer interactionnetworks and to predict the biological process that the protein is involved in.Here, we develop a probabilistic approach for protein function prediction usingnetwork data, such as protein-protein interaction measurements. We take aBayesian approach to an existing Markov Random Field method by performingsimultaneous estimation of the model parameters and prediction of proteinfunctions. We use an adaptive Markov Chain Monte Carlo algorithm that leads tomore accurate parameter estimates and consequently to improved predictionperformance compared to the standard Markov Random Fields method. We tested ourmethod using a high quality S.cereviciae validation networkwith 1622 proteins against 90 Gene Ontology terms of different levels ofabstraction. Compared to three other protein function prediction methods, ourapproach shows very good prediction performance. Our method can be directlyapplied to protein-protein interaction or coexpression networks, but also can beextended to use multiple data sources. We apply our method to physical proteininteraction data from S. cerevisiae and provide novelpredictions, using 340 Gene Ontology terms, for 1170 unannotated proteins and weevaluate the predictions using the available literature.