<Emphasis Type="Italic">MEFV</Emphasis> mutations in patients with familial Mediterranean fever from the Aegean region of Turkey

Familial Mediterranean Fever (FMF) which is frequently present in Mediterranean populations is caused by mutations in the MEFV gene. According to recent data, MEFV mutations are not the only cause of FMF, but these are major genetic determinants which cause FMF. It has also been suggested that there may be a number of other genes causing FMF. The MEFV gene is located at 16p13.3 and encodes a protein, pyrin/marenostrin. More than 70 disease associated mutations and totally 186 mutations and polymorphisms have been defined in affected individuals. We have retrospectively evaluated the molecular test results of 1,201 patients identified as having FMF clinical symptoms referred to the Molecular Genetics Laboratory of the Department of Medical Genetics, Faculty of Medicine, Ege University, Izmir/Turkey over the last 4 years. Patients were tested for 12 common mutations in the MEFV gene using a strip assay method (Innogenetics, Belgium). Out of the 1,201 patients tested (2,402 chromosomes) in the Aegean region in Turkey, 654 (54.45%) did not carry any mutations, among the 547 (45.55%) patients with mutations 246 patients were either homozygous (101) or compound heterozygous (145), 296 carried only one detected mutation, and five patients had three mutations. Allelic frequencies for the four most common mutations in the mutation positive groups were 47.60% (M694V), 16.75% (E148Q), 12.95% (V726A), 11.94% (M680I G/C).The remaining alleles (10.76%) showed rare mutations which were R761H, P369S, A744S, K695R, F479L, M694I. When the frequencies of mutations detected in our group were compared to the frequencies reported in the other regions of Turkey, an increase in V726A mutation frequency was observed. No patient showed a I692del mutation which is sometimes evident in other Mediterranean populations.     

Reciprocal inhibition of G-protein signaling is induced by CB(1) cannabinoid and GABA(B) receptor interactions in rat hippocampal membranes

Cannabinoid CB(1) and the metabotropic GABA(B) receptors have been shown to display similar pharmacological effects and co-localization in certain brain regions. Previous studies have reported a functional link between the two systems. As a first step to investigate the underlying molecular mechanism, here we show cross-inhibition of G-protein signaling between GABA(B) and CB(1) receptors in rat hippocampal membranes. The CB(1) agonist R-Win55,212-2 displayed high potency and efficacy in stimulating guanosine-5'-O-(3-[(35)S]thio)triphosphate, [(35)S]GTPgammaS binding. Its effect was completely blocked by the specific CB(1) antagonist AM251 suggesting that the signaling was via CB(1) receptors. The GABA(B) agonists baclofen and SKF97541 also elevated [(35)S]GTPgammaS binding by about 60%, with potency values in the micromolar range. Phaclofen behaved as a low potency antagonist with an ED(50) approximately 1mM. However, phaclofen at low doses (1 and 10nM) slightly but significantly attenuated maximal stimulation of [(35)S]GTPgammaS binding by the CB(1) agonist R-Win55,212-2. The observation that higher concentrations of phaclofen had no such effect rule out the possibility of its direct action on CB(1) receptors. The pharmacologically inactive stereoisomer S-Win55,212-3 had no effect either alone or in combination with phaclofen establishing that the interaction is stereospecific in hippocampus. The specific CB(1) antagonist AM251 at a low dose (1 nM) also inhibited the efficacy of G-protein signaling of the GABA(B) receptor agonist SKF97541. Cross-talk of the two receptor systems was not detected in either spinal cord or cerebral cortex membranes. It is speculated that the interaction might occur via an allosteric interaction between a subset of GABA(B) and CB(1) receptors in rat hippocampal membranes. Although the exact molecular mechanism of the reciprocal inhibition between CB(1) and GABA(B) receptors will have to be explored by future studies it is intriguing that the cross-talk might be involved in balance tuning the endocannabinoid and GABAergic signaling in hippocampus.     

Radiation-induced genomic instability: a role for secreted soluble factors in communicating the radiation response to non-irradiated cells

Radiation induced genomic instability can be described as the increased rate of genomic alterations occurring in the progeny of an irradiated cell. Its manifestations are the dynamic ongoing production of chromosomal rearrangements, mutations, gene amplifications, transformation, microsatellite instability, and/or cell killing. In this prospectus, we present the hypothesis that cellular exposure to ionizing radiation can result in the secretion of soluble factors by irradiated cells and/or their progeny, and that these factors can elicit responses in other cells thereby initiating and perpetuating ongoing genomic instability.     

Quantifying biofilm structure: facts and fiction

There is no doubt among biofilm researchers that biofilm structure is important to many biofilm processes, such as the transport of nutrients to deeper layers of the biofilm. However, biofilm structure is an elusive term understood only qualitatively, and as such it cannot be directly correlated with any measurable parameters characterizing biofilm performance. To correlate biofilm structure with the parameters characterizing biofilm performance, such as the rate of nutrient transport within the space occupied by the biofilms, biofilm structure must first be quantified and expressed numerically on an appropriate scale. The task of extracting numerical parameters quantifying biofilm structure relies on using biofilm imaging and image analysis. Although defining parameters characterizing biofilm structure is relatively straightforward, and multiple parameters have been described in the computer science literature, interpreting the results of such analyses is not trivial. Existing computer software developed by several research groups, including ours, for the sole purpose of analyzing biofilm images helps quantify parameters from biofilm images but does nothing to help interpret the results of such analyses. Although computing structural parameters from biofilm images permits correlating biofilm structure with other biofilm processes, the meaning of the results is not obvious. The first step to understanding the quantification of biofilm structure, developing image analysis, methods to quantify information from biofilm images, has been made by several research groups. The next step is to explain the meaning of these analyses. This presentation explains the meaning of several parameters commonly used to characterize biofilm structure. It also reviews the authors' research and experience in quantifying biofilm structure and their attempts to quantitatively relate biofilm structure to fundamental biofilm processes.     

An integrated model of epidermal growth factor receptor trafficking and signal transduction

Endocytic trafficking of many types of receptors can have profound effects on subsequent signaling events. Quantitative models of these processes, however, have usually considered trafficking and signaling independently. Here, we present an integrated model of both the trafficking and signaling pathway of the epidermal growth factor receptor (EGFR) using a probability weighted-dynamic Monte Carlo simulation. Our model consists of hundreds of distinct endocytic compartments and approximately 13,000 reactions/events that occur over a broad spatio-temporal range. By using a realistic multicompartment model, we can investigate the distribution of the receptors among cellular compartments as well as their potential signal transduction characteristics. Our new model also allows the incorporation of physiochemical aspects of ligand-receptor interactions, such as pH-dependent binding in different endosomal compartments. To determine the utility of this approach, we simulated the differential activation of the EGFR by two of its ligands, epidermal growth factor (EGF) and transforming growth factor-alpha (TGF-alpha). Our simulations predict that when EGFR is activated with TGF-alpha, receptor activation is biased toward the cell surface whereas EGF produces a signaling bias toward the endosomal compartment. Experiments confirm these predictions from our model and simulations. Our model accurately predicts the kinetics and extent of receptor downregulation induced by either EGF or TGF-alpha. Our results suggest that receptor trafficking controls the compartmental bias of signal transduction, rather than simply modulating signal magnitude. Our model provides a new approach to evaluating the complex effect of receptor trafficking on signal transduction. Importantly, the stochastic and compartmental nature of the simulation allows these models to be directly tested by high-throughput approaches, such as quantitative image analysis.     

Determination of poly-β-hydroxybutyrate (PHB) production by some <Emphasis Type="Italic">Bacillus</Emphasis> spp.

In this study, 29 strains of the genus Bacillus were isolated from different soil samples which were taken from grasslands of Ankara, Turkey and were identified as B. brevis, B. sphaericus, B. cereus, B. megaterium, B. circulans, B. subtilis, B. licheniformis and B. coagulans. Two strains, B. sphaericus ATCC 14577 and B. subtilis ATCC 6633 were also included in this study. Poly-β-hydroxybutyrate (PHB) production by these strains was determined by the spectrophotometric method, and it was found that PHB production ranged from 1.06–41.67% (w/v) depending on the dry cell weight. The highest PHB production and productivity percentage was found in B. brevis M6 (41.67% w/v).     

Comparative molecular dynamics simulations of amphotericin B-cholesterol/ergosterol membrane channels

Amphotericin B (AmB) is a very effective anti-fungal polyene macrolide antibiotic whose usage is limited by its toxicity. Lack of a complete understanding of AmB's molecular mechanism has impeded attempts to design less toxic AmB derivatives. The antibiotic is known to interact with sterols present in the cell membrane to form ion channels that disrupt membrane function. The slightly higher affinity of AmB toward ergosterol (dominant sterol in fungal cells) than cholesterol (mammalian sterol) is regarded as the most essential factor on which antifungal chemotherapy is based. To study these differences at the molecular level, two realistic model membrane channels containing molecules of AmB, sterol (cholesterol or ergosterol), phospholipid, and water were studied by molecular dynamics (MD) simulations. Comparative analysis of the simulation data revealed that the sterol type has noticeable effect on the properties of AmB membrane channels. In addition to having a larger size, the AmB channel in the ergosterol-containing membrane has a more pronounced pattern of intermolecular hydrogen bonds. The interaction between the antibiotic and ergosterol is more specific than between the antibiotic and cholesterol. These observed differences suggest that the channel in the ergosterol-containing membrane is more stable and, due to its larger size, would have a higher ion conductance. These observations are in agreement with experiments.     

PER-1 is still widespread in Turkish hospitals among Pseudomonas aeruginosa and Acinetobacter spp

PER-1 type beta-lactamases were screened among ceftazidime-resistant clinical isolates of Acinetobacter spp. and Pseudomonas aeruginosa. A total of 176 non-repetitive isolates (84 Acinetobacter spp. and 92 P. aeruginosa) were collected during a three month surveillance period. Isolates were obtained from seven intensive care units of seven university hospitals. All strains were screened for bla(PER-1) alleles by PCR. Of the strains, 31% and 55.4% of Acinetobacter spp. and P. aeruginosa were positive for bla(PER-1) type genes, respectively.     

Internal and external mass transfer in biofilms grown at various flow velocities

It appears that biofilms arrange their internal structure according to the flow velocity at which they are grown, which affects the internal mass transfer rate and microbial activity. In biofilms grown at various flow velocities we determined the vertical profiles of the local relative effective diffusivity (termed D(l)) at several locations within each biofilm. From these profiles we calculated the surface-averaged relative effective diffusivity (termed D(sa)) at various distances from the bottom and plotted it against these distances. The D(sa) decreased linearly toward the bottom, forming well-defined profiles that were different for each biofilm. The gradients of these profiles were multiplied by the diffusivity of oxygen, zeta = D(w) dD(sa)/dz, and plotted versus the flow velocity at which each biofilm was grown. The gradients were low at flow velocities below 10 cm/s, reached a maximum at a flow velocity of 10 cm/s, and decreased again at flow velocities exceeding 10 cm/s. The existence of a maximum indicates a possibility that two opposing forces were affecting the slope of the profiles. To explain these observations we hypothesized that biofilms, depending on the flow velocity at which they are grown, arrange their internal architecture to control (1) the nutrient transport rate and (2) the mechanical pliability needed to resist the shear stress of the water flowing past them. It appears that biofilms attempt to satisfy the second goal first, to increase their mechanical strength, and that they do so at the expense of the nutrient transfer rate to deeper layers. This strength increase is associated with an increase in biofilm density, which slows down the internal mass transport rate. Biofilms grown at low flow velocities exhibit low density and high effective diffusivity but cannot resist higher shear stress, whereas biofilms grown at higher flow velocities are denser and can resist higher shear stress but have a lower effective diffusivity.